Last updated: 2020-08-05

Checks: 6 1

Knit directory: HiCiPSC/

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    Modified:   analysis/TADs.Rmd
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    Modified:   analysis/enrichment.Rmd

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These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File Version Author Date Message
Rmd 75e11d0 Ittai Eres 2020-08-05 Update formatting for headers
html ae66f6e Ittai Eres 2019-06-27 Build site.
Rmd a15345d Ittai Eres 2019-06-27 Update index and corresponding figure references to match final version of paper.
html 5fda2d6 Ittai Eres 2019-06-25 Build site.
html 2ec8067 Ittai Eres 2019-05-09 Build site.
html ff886b1 Ittai Eres 2019-04-30 Build site.
html db4d599 Ittai Eres 2019-04-25 Build site.
html 6f6db11 Ittai Eres 2019-04-23 Build site.
html a02a602 Ittai Eres 2019-03-14 Build site.
Rmd a6451a3 Ittai Eres 2019-03-14 Add gene expression overlay (still needs more modification); update index

First, load necessary libraries: limma, plyr, tidyr, data.table, reshape2, cowplot, plotly, dplyr, Hmisc, gplots, stringr, heatmaply, RColorBrewer, edgeR, tidyverse, and compiler

Preparing the gene expression data

Here I read in a dataframe of counts summarized at the gene-level, then do some pre-processing and normalization to obtain a voom object to later run linear modeling analyses on.

#Read in counts data, create DGEList object out of them and convert to log counts per million (CPM). Also read in metadata.
setwd("/Users/ittaieres/HiCiPSC")
counts <- fread("data/counts_iPSC.txt", header=TRUE, data.table=FALSE, stringsAsFactors = FALSE, na.strings=c("NA",""))
colnames(counts) <- c("genes", "C-3649", "G-3624", "H-3651", "D-40300", "F-28834", "B-28126", "E-28815", "A-21792")
rownames(counts) <- counts$genes
counts <- counts[,-1]
dge <- DGEList(counts, genes=rownames(counts))

#Now, convert counts into RPKM to account for gene length differences between species. First load in and re-organize metadata, then the gene lengths for both species, and then the function to convert counts to RPKM.
meta_data <- fread("data/Meta_data.txt", sep="\t",stringsAsFactors = FALSE,header=T,na.strings=c("NA",""))
meta_data$fullID <- c("C-3649", "H-3651", "B-28126", "D-40300", "G-3624", "A-21792", "E-28815", "F-28834")
ord <- data.frame(fullID=colnames(counts)) #Pull order of samples from expression object
left_join(ord, meta_data, by="fullID") -> group_ref #left join meta data to this to make sure sample IDs correct
Warning: Column `fullID` joining factor and character vector, coercing into
character vector
#Read in human and chimp gene lengths for the RPKM function:
human_lengths<- fread("data/human_lengths.txt", sep="\t",stringsAsFactors = FALSE,header=T,na.strings=c("NA",""))
chimp_lengths<- fread("data/chimp_lengths.txt", sep="\t",stringsAsFactors = FALSE,header=T,na.strings=c("NA",""))

#The function for RPKM conversion.
vRPKM <- function(expr.obj,chimp_lengths,human_lengths,meta4) {
  if (is.null(expr.obj$E)) {
    meta4%>%filter(SP=="C" & fullID %in% colnames(counts))->chimp_meta
    meta4%>%filter(SP=="H" & fullID %in% colnames(counts))->human_meta
    
    #using RPKM function:
    #Put genes in correct order:
    expr.obj$genes %>%select(Geneid=genes)%>%
      left_join(.,chimp_lengths,by="Geneid")%>%select(Geneid,ch.length)->chlength
    
    expr.obj$genes %>%select(Geneid=genes)%>%
      left_join(.,human_lengths,by="Geneid")%>%select(Geneid,hu.length)->hulength
    
    #Chimp RPKM
    expr.obj$genes$Length<-(chlength$ch.length)
    RPKMc=rpkm(expr.obj,normalized.lib.sizes=TRUE, log=TRUE)
    RPKMc[,colnames(RPKMc) %in% chimp_meta$fullID]->rpkm_chimp
    
    #Human RPKM
    expr.obj$genes$Length<-hulength$hu.length
    RPKMh=rpkm(expr.obj,normalized.lib.sizes=TRUE, log=TRUE)
    RPKMh[,colnames(RPKMh) %in% human_meta$fullID]->rpkm_human
    
    
    cbind(rpkm_chimp,rpkm_human)->allrpkm
    expr.obj$E <- allrpkm
    return(expr.obj)
    
  }
  else {
    #Pull out gene order from voom object and add in gene lengths from feature counts file
    #Put genes in correct order:
    expr.obj$genes %>%select(Geneid=genes)%>%
      left_join(.,chimp_lengths,by="Geneid")%>%select(Geneid,ch.length)->chlength
    
    expr.obj$genes %>%select(Geneid=genes)%>%
      left_join(.,human_lengths,by="Geneid")%>%select(Geneid,hu.length)->hulength
    
    
    #Filter meta data to be able to separate human and chimp
    meta4%>%filter(SP=="C")->chimp_meta
    meta4%>%filter(SP=="H")->human_meta
    
    #Pull out the expression data in cpm to convert to RPKM
    expr.obj$E->forRPKM
    
    forRPKM[,colnames(forRPKM) %in% chimp_meta$fullID]->rpkm_chimp
    forRPKM[,colnames(forRPKM) %in% human_meta$fullID]->rpkm_human
    
    #Make log2 in KB:
    row.names(chlength)=chlength$Geneid
    chlength %>% select(-Geneid)->chlength
    as.matrix(chlength)->chlength
    
    row.names(hulength)=hulength$Geneid
    hulength %>% select(-Geneid)->hulength
    as.matrix(hulength)->hulength
    
    log2(hulength/1000)->l2hulength
    log2(chlength/1000)->l2chlength
    
    
    #Subtract out log2 kb:
    sweep(rpkm_chimp, 1,l2chlength,"-")->chimp_rpkm
    sweep(rpkm_human, 1,l2hulength,"-")->human_rpkm
    
    colnames(forRPKM)->column_order
    
    cbind(chimp_rpkm,human_rpkm)->vRPKMS
    #Put RPKMS back into the VOOM object:
    expr.obj$E <- (vRPKMS[,colnames(vRPKMS) %in% column_order])
    return(expr.obj)
  }
}

dge <- vRPKM(dge, chimp_lengths, human_lengths, group_ref) #Normalize via log2 RPKM.

#A typical low-expression filtering step: use default prior count adding (0.25), and filtering out anything that has fewer than half the individuals within each species having logCPM less than 1.5 (so want 2 humans AND 2 chimps with log2CPM >= 1.5)
lcpms <- cpm(dge$counts, log=TRUE) #Obtain log2CPM!
good.chimps <- which(rowSums(lcpms[,1:4]>=1.5)>=2) #Obtain good chimp indices
good.humans <- which(rowSums(lcpms[,5:8]>=1.5)>=2) #Obtain good human indices
filt <- good.humans[which(good.humans %in% good.chimps)] #Subsets us down to a solid 11,292 genes--will go for a similar percentage with RPKM cutoff vals! (25.6% of total)

#Repeat filtering step, this time on RPKMs. 0.4 was chosen as a cutoff as it obtains close to the same results as 1.5 lcpm (in terms of percentage of genes retained)
good.chimps <- which(rowSums(dge$E[,1:4]>=0.4)>=2) #Obtain good chimp indices.
good.humans <- which(rowSums(dge$E[,5:8]>=0.4)>=2) #Obtain good human indices.
RPKM_filt <- good.humans[which(good.humans %in% good.chimps)] #Still leaves us with 11,946 genes (27.1% of total)

#Do the actual filtering.
dge_filt <- dge[RPKM_filt,]
dge_filt$E <- dge$E[RPKM_filt,]
dge_filt$counts <- dge$counts[RPKM_filt,]
dge_filt$lcpm_counts <- cpm(dge$counts, log=TRUE)[RPKM_filt,] #Add this in to be able to look at log cpms later
dge_final <- calcNormFactors(dge_filt, method="TMM") #Calculate normalization factors with trimmed mean of M-values (TMM).
dge_norm <- calcNormFactors(dge, method="TMM") #Calculate normalization factors with TMM on dge before filtering out lowly expressed genes, for normalization visualization.

#Quick visualization of the filtering I've just performed:
col <- brewer.pal(8, "Paired")
par(mfrow=c(1,2))
plot(density(dge$E[,1]), col=col[1], lwd=2, ylim=c(0,0.35), las=2, 
     main="", xlab="")
title(main="A. Raw data", xlab="Log-RPKM")
abline(v=1, lty=3)
for (i in 2:8){
 den <- density(dge$E[,i])
 lines(den$x, den$y, col=col[i], lwd=2)
}
legend("topright", colnames(dge$E[,1:8]), text.col=col, bty="n")

plot(density(dge_final$E[,1]), col=col[1], lwd=2, ylim=c(0,0.35), las=2, 
     main="", xlab="")
title(main="B. Filtered data", xlab="Log-RPKM")
abline(v=1, lty=3)
for (i in 2:8){
   den <- density(dge_final$E[,i])
   lines(den$x, den$y, col=col[i], lwd=2)
}
legend("topright", colnames(dge_final[,1:8]), text.col=col, bty="n")

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#Quick visualization of the normalization on the whole set of genes.
col <- brewer.pal(8, "Paired")
raw <- as.data.frame(dge$E[,1:8])
normed <- as.data.frame(dge_norm$E[,1:8])
par(mfrow=c(1,2))
boxplot(raw, las=2, col=col, main="")
title(main="Unnormalized data",ylab="Log-RPKM")
boxplot(normed, las=2, col=col, main="")
title(main="Normalized data",ylab="Log-RPKM")

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#Now, observe normalization on the filtered set of genes.
col <- brewer.pal(8, "Paired")
raw <- as.data.frame(dge_filt$E[,1:8])
normed <- as.data.frame(dge_final$E[,1:8])
par(mfrow=c(1,2))
boxplot(raw, las=2, col=col, main="")
title(main="Unnormalized data",ylab="Log-RPKM")
boxplot(normed, las=2, col=col, main="")
title(main="Normalized data",ylab="Log-RPKM")

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#Now, do some quick MDS plotting to make sure this expression data separates out species properly.
species <- c("C", "C", "C", "C", "H", "H", "H", "H")
color <- c(rep("red", 4), rep("blue", 4))
par(mfrow=c(1,1))
plotMDS(dge_final$E[,1:8], labels=species, col=color, main="MDS Plot") #Shows separation of the species along the logFC dimension representing the majority of the variance--orthogonal check to PCA, and looks great!

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###Now, apply voom to get quality weights.
meta.exp.data <- data.frame("SP"=c("C", "C", "C", "C", "H", "H", "H", "H"), "SX"=c("M","M" ,"F","F","F", "M","M","F"))
SP <- factor(meta.exp.data$SP,levels = c("H","C"))
SX <- factor(meta.exp.data$SX, levels=c("M", "F"))
exp.design <- model.matrix(~0+SP+SX) #Include both species and sex as covariates.
colnames(exp.design) <- c("Human", "Chimp", "Sex")
weighted.data <- voom(dge_final, exp.design, plot=TRUE, normalize.method = "cyclicloess")

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##Obtain rest of LM results, with particular eye to DE table!
vfit <- lmFit(weighted.data, exp.design)
efit <- eBayes(vfit)

mycon <- makeContrasts(HvC = Human-Chimp, levels = exp.design)
diff_species <- contrasts.fit(efit, mycon)
finalfit <- eBayes(diff_species)
detable <- topTable(finalfit, coef = 1, adjust.method = "BH", number = Inf, sort.by="none")
plotSA(efit, main="Final model: Mean−variance trend")

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#Get lists of the DE and non-DE genes so I can run separate analyses on them at any point.
DEgenes <- detable$genes[which(detable$adj.P.Val<=0.05)]
nonDEgenes <- detable$genes[-which(detable$adj.P.Val<=0.05)]

#Rearrange RPKM and weight columns in voom object to be similar to the rest of my setup throughout in other dataframes.
weighted.data$E <- weighted.data$E[,c(8, 6, 1, 4, 7, 5, 2, 3)]
weighted.data$weights <- weighted.data$weights[,c(8, 6, 1, 4, 7, 5, 2, 3)]
RPKM <- as.data.frame(weighted.data$E)
RPKM$genes <- rownames(RPKM) #Just to match what I had before on midway2, about to write this out.
saveRDS(RPKM, file="output/IEE.RPKM.RDS")
saveRDS(weighted.data, file="output/IEE_voom_object.RDS") #write this object out, can then be read in with readRDS.

Overlap Between Hi-C Data and Orthogonal Gene Expression Data

In this section I find the overlap between the final filtered set of Hi-C significant hits and genes picked up on by an orthogonal RNA-seq experiment in the same set of cell lines. I utilize an in-house curated set of orthologous genes between humans and chimpanzees. Given that the resolution of the data is 10kb, I choose a simple and conservative approach and use a 1-nucleotide interval at the start of each gene as a proxy for the promoter. I then take a conservative pass and only use genes that had direct overlap with a bin from the Hi-C significant hits data, with more motivation explained below.

#Now, read in filtered data from linear_modeling_QC.Rmd.
data.filtered <- fread("output/data.4.filtered.lm.QC", header=TRUE, data.table=FALSE, stringsAsFactors = FALSE, showProgress=FALSE)
meta.data <- data.frame("SP"=c("H", "H", "C", "C", "H", "H", "C", "C"), "SX"=c("F", "M", "M", "F", "M", "F", "M", "F"), "Batch"=c(1, 1, 1, 1, 2, 2, 2, 2))


###Grab DC and non-DC Example Interactions from Data### For creating FIG3 and FIGS7
great.indices <- which(data.filtered$sp_BH_pval<=0.05&data.filtered$dist_diff<=10000&data.filtered$Hdist<=150000&data.filtered$disc_species=="B"&data.filtered$Hdist>=50000)
mydat <- data.filtered[great.indices,]
mydat <- select(mydat, sp_BH_pval, sp_beta, Hchr, H1, H2, Cchr, C1, C2, Hmean, Cmean, dist_diff, Hdist, Cdist)
mydat <- mydat[order(mydat$sp_BH_pval),]
which.max(mydat$sp_beta)
[1] 29
weak.indices <- which(data.filtered$sp_BH_pval>=0.95&data.filtered$dist_diff<=10000&data.filtered$Hdist<=150000&data.filtered$disc_species=="B"&data.filtered$Hdist>=50000)
mydat <- data.filtered[weak.indices,]
mydat <- select(mydat, sp_BH_pval, sp_beta, Hchr, H1, H2, Cchr, C1, C2, Hmean, Cmean, dist_diff, Hdist, Cdist)
mydat <- mydat[order(mydat$Hmean, decreasing = TRUE),]
##

#TABLES1
#Write out data.filtered regions that are DC for supplementary table:
TABLES1 <- select(data.filtered, H1, H2, C1, C2, sp_BH_pval, sp_beta) %>% filter(., sp_BH_pval<=0.05)
TABLES1$Hchr <- gsub("-.*", "", TABLES1$H1)
TABLES1$H1start <- as.numeric(gsub(".*-", "", TABLES1$H1))
TABLES1$H1end <- TABLES1$H1start+10000
TABLES1$H2start <- as.numeric(gsub(".*-", "", TABLES1$H2))
TABLES1$H2end <- TABLES1$H2start+10000
TABLES1$Cchr <- gsub("-.*", "", TABLES1$C1)
TABLES1$C1start <- as.numeric(gsub(".*-", "", TABLES1$C1))
TABLES1$C1end <- TABLES1$C1start+10000
TABLES1$C2start <- as.numeric(gsub(".*-", "", TABLES1$C2))
TABLES1$C2end <- TABLES1$C2start+10000

select(TABLES1, Hchr, H1start, H1end, H2start, H2end, Cchr, C1start, C1end, C2start, C2end, sp_BH_pval, sp_beta) -> TABLES1
fwrite(TABLES1, "output/DC_regions.txt", col.names = TRUE, row.names = FALSE, sep = "\t")

#####GENE Hi-C Hit overlap: First, I obtain and rearrange the necessary files to get genes from both species and their overlaps with Hi-C bins.
#Read in necessary files: human and chimp orthologous genes from the meta ortho exon trios file. Then rearrange the columns of humgenes and chimpgenes to use group_by on them.
humgenes <- fread("data/Human_orthoexon_extended_info.txt", stringsAsFactors = FALSE, header=TRUE, data.table=FALSE)
chimpgenes <- fread("data/Chimp_orthoexon_extended_info.txt", stringsAsFactors = FALSE, header=TRUE, data.table=FALSE)
humgenes <- as.data.frame(humgenes[,c(1,5:8)])
chimpgenes <- as.data.frame(chimpgenes[,c(1,5:8)])
colnames(humgenes) <- c("genes", "Hchr", "Hstart", "Hend", "Hstrand")
colnames(chimpgenes) <- c("genes", "Cchr", "Cstart", "Cend", "Cstrand")
humgenes$Hchr <- paste("chr", humgenes$Hchr, sep="") #All properly formatted now!

#Bedtools groupby appears to have not worked properly to create files of single TSSs for genes from the meta ortho exons file, but this totally does! I've also utilized dplyr's group_by on the original file as well to ensure the same results. Now just making gene BED files that are 1-nt overlap at the very beginning of the first exon. Since I maintain strand information and will utilize it in bedtools closest-to, I am not concerned about whether the nt overlap goes the right direction or not. Note that if plyr is accidentally loaded AFTER dplyr, this will have issues (periods added at the end of start coords):
group_by(humgenes, genes) %>% summarise(Hchr=unique(Hchr), Hstart=as.numeric(min(Hstart)), Hend=Hstart+1, Hstrand=unique(Hstrand), holder=".") -> humgenes
group_by(chimpgenes, genes) %>% summarise(Cchr=unique(Cchr), Cstart=min(Cstart), Cend=Cstart+1, Cstrand=unique(Cstrand), holder=".") -> chimpgenes

#Format both of these properly for how the code was previously written.
humgenes <- humgenes[,c(2:4, 1, 6, 5)]
chimpgenes <- chimpgenes[,c(2:4,1, 6, 5)]

#Now, prep bed files from the filtered data for each bin, in order to run bedtools-closest on them with the human and chimp gene data. This is for getting each bin's proximity to TSS by overlapping with the dfs just made (humgenes and chimpgenes). In the end this set of bedfiles is fairly useless, because really it would be preferable to get rid of duplicates so that I can merely group_by on a given bin afterwards and left_join as necessary. So somewhat deprecated, but I keep it here still:
hbin1 <- data.frame(chr=data.filtered$Hchr, start=as.numeric(gsub("chr.*-", "", data.filtered$H1)), end=as.numeric(gsub("chr.*-", "", data.filtered$H1))+10000)
hbin2 <- data.frame(chr=data.filtered$Hchr, start=as.numeric(gsub("chr.*-", "", data.filtered$H2)), end=as.numeric(gsub("chr.*-", "", data.filtered$H2))+10000)
cbin1 <- data.frame(chr=data.filtered$Cchr, start=as.numeric(gsub("chr.*-", "", data.filtered$C1)), end=as.numeric(gsub("chr.*-", "", data.filtered$C1))+10000)
cbin2 <- data.frame(chr=data.filtered$Cchr, start=as.numeric(gsub("chr.*-", "", data.filtered$C2)), end=as.numeric(gsub("chr.*-", "", data.filtered$C2))+10000)

#In most analyses, it will make more sense to have a single bed file for both sets of bins, and remove all duplicates. I create that here:
hbins <- rbind(hbin1[!duplicated(hbin1),], hbin2[!duplicated(hbin2),])
hbins <- hbins[!duplicated(hbins),]
cbins <- rbind(cbin1[!duplicated(cbin1),], cbin2[!duplicated(cbin2),])
cbins <- cbins[!duplicated(cbins),]

#Need to reformat hbins here for proper bedtools use:
hbins$chr <- gsub("Chr. ", "chr", hbins$chr) #All good.

#Now, write all of these files out for analysis with bedtools.
options(scipen=999)
#write.table(hbin1, "~/Desktop/Hi-C/gene_expression/10kb_filt_overlaps/unsorted/hbin1.bed", quote = FALSE, sep="\t", row.names = FALSE, col.names=FALSE)
#write.table(hbin2, "~/Desktop/Hi-C/gene_expression/10kb_filt_overlaps/unsorted/hbin2.bed", quote = FALSE, sep="\t", row.names = FALSE, col.names=FALSE)
#write.table(cbin1, "~/Desktop/Hi-C/gene_expression/10kb_filt_overlaps/unsorted/cbin1.bed", quote = FALSE, sep="\t", row.names = FALSE, col.names=FALSE)
#write.table(cbin2, "~/Desktop/Hi-C/gene_expression/10kb_filt_overlaps/unsorted/cbin2.bed", quote = FALSE, sep="\t", row.names = FALSE, col.names=FALSE)
write.table(humgenes, "data/hic_gene_overlap/humgenes.bed", quote=FALSE, sep="\t", row.names=FALSE, col.names=FALSE)
write.table(chimpgenes, "data/hic_gene_overlap/chimpgenes.bed", quote=FALSE, sep="\t", row.names=FALSE, col.names=FALSE)
write.table(hbins, "data/hic_gene_overlap/hbins.bed", quote=FALSE, sep="\t", row.names=FALSE, col.names=FALSE)
write.table(cbins, "data/hic_gene_overlap/cbins.bed", quote=FALSE, sep="\t", row.names=FALSE, col.names=FALSE)
options(scipen=0)

#Read in new, simpler bedtools closest files for genes. This is after running two commands, after sorting the files w/ sort -k1,1 -k2,2n in.bed > out.bed:
#bedtools closest -D a -a cgenes.sorted.bed -b cbins.sorted.bed > cgene.hic.overlap
#bedtools closest -D a -a hgenes.sorted.bed -b hbins.sorted.bed > hgene.hic.overlap
#A bash file showing this is included in the data/hic_gene_overlap directory (overlapper.sh)
hgene.hic <- fread("data/hic_gene_overlap/hgene.hic.overlap", header=FALSE, stringsAsFactors = FALSE, data.table=FALSE)
cgene.hic <- fread("data/hic_gene_overlap/cgene.hic.overlap", header=FALSE, stringsAsFactors = FALSE, data.table=FALSE)


#Visualize the overlap of genes with bins and see how many genes we get back!
hum.genelap <- data.frame(overlap=seq(0, 100000, 1000), perc.genes = NA, tot.genes=NA)
for(row in 1:nrow(hum.genelap)){
  hum.genelap$perc.genes[row] <- sum(abs(hgene.hic$V10)<=hum.genelap$overlap[row])/length(hgene.hic$V10)
  hum.genelap$tot.genes[row] <- sum(abs(hgene.hic$V10)<=hum.genelap$overlap[row])
}

c.genelap <- data.frame(overlap=seq(0, 100000, 1000), perc.genes=NA, tot.genes=NA)
for(row in 1:nrow(c.genelap)){
  c.genelap$perc.genes[row] <- sum(abs(cgene.hic$V10)<=c.genelap$overlap[row])/length(cgene.hic$V10)
  c.genelap$tot.genes[row] <- sum(abs(cgene.hic$V10)<=c.genelap$overlap[row])
}
c.genelap$type <- "chimp"
hum.genelap$type <- "human"

#Examine what the potential gains are here if we are more lenient about the overlap/closeness to a TSS...
ggoverlap <- rbind(hum.genelap, c.genelap)
ggplot(data=ggoverlap) + geom_line(aes(x=overlap, y=perc.genes*100, color=type)) + ggtitle("Percent of Total Genes Picked Up | Min. Distance from TSS") + xlab("Distance from TSS") + ylab("Percentage of genes in ortho exon trios file (~44k)") + scale_color_discrete(guide=guide_legend(title="Species")) + coord_cartesian(xlim=c(0, 30000)) + scale_x_continuous(breaks=seq(0, 30000, 5000))

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ggplot(data=ggoverlap) + geom_line(aes(x=overlap, y=tot.genes, color=type)) + ggtitle("Total # Genes Picked Up | Min. Distance from TSS") + xlab("Distance from TSS") + ylab("Total # of Genes Picked up On (of ~44k)") + scale_color_discrete(guide=guide_legend(title="Species")) + coord_cartesian(xlim=c(0, 30000)) + scale_x_continuous(breaks=seq(0, 30000, 5000))

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a02a602 Ittai Eres 2019-03-14
#Start with a conservative pass--only take those genes that had an actual overlap with a bin, not ones that were merely close to one. Allowing some leeway to include genes that are within 1kb, 2kb, 3kb etc. of a Hi-C bin adds an average of ~800 genes per 1kb. We can also examine the distribution manually to motivate this decision:
quantile(abs(hgene.hic$V10), probs=seq(0, 1, 0.025))
       0%      2.5%        5%      7.5%       10%     12.5%       15% 
      0.0       0.0       0.0       0.0       0.0       0.0       0.0 
    17.5%       20%     22.5%       25%     27.5%       30%     32.5% 
      0.0       0.0       0.0       0.0       0.0       0.0       0.0 
      35%     37.5%       40%     42.5%       45%     47.5%       50% 
      0.0       0.0       0.0       0.0       0.0       0.0       0.0 
    52.5%       55%     57.5%       60%     62.5%       65%     67.5% 
      0.0       0.0       0.0     435.4    1741.0    2968.2    4324.0 
      70%     72.5%       75%     77.5%       80%     82.5%       85% 
   6226.2    8868.0   12336.0   16610.0   22034.4   29271.5   38300.2 
    87.5%       90%     92.5%       95%     97.5%      100% 
  50248.0   67698.4   92599.2  135125.0  243068.9 7581822.0 
quantile(abs(cgene.hic$V10), probs=seq(0, 1, 0.025))
        0%       2.5%         5%       7.5%        10%      12.5% 
       0.0        0.0        0.0        0.0        0.0        0.0 
       15%      17.5%        20%      22.5%        25%      27.5% 
       0.0        0.0        0.0        0.0        0.0        0.0 
       30%      32.5%        35%      37.5%        40%      42.5% 
       0.0        0.0        0.0        0.0        0.0        0.0 
       45%      47.5%        50%      52.5%        55%      57.5% 
       0.0        0.0        0.0        0.0        0.0        0.0 
       60%      62.5%        65%      67.5%        70%      72.5% 
     237.4     1507.0     2800.0     4237.4     6125.6     8750.4 
       75%      77.5%        80%      82.5%        85%      87.5% 
   12181.0    16648.0    22317.4    29420.0    38490.0    50656.0 
       90%      92.5%        95%      97.5%       100% 
   67470.4    92415.3   136417.4   243285.0 21022081.0 
#Note I looked at proportion of overlap with DE and with non-DE genes just for curiosity, and roughly 66% of the DE genes have overlap with a Hi-C bin while roughly 70% of the non-DE genes do. Since this result isn't particularly interesting I have collapsed that analysis here.
#Also are interested in seeing how this differs for DE and non-DE genes.
dehgene.hic <- hgene.hic[which(hgene.hic$V4 %in% DEgenes),]
decgene.hic <- cgene.hic[which(cgene.hic$V4 %in% DEgenes),]
nondehgene.hic <- hgene.hic[which(hgene.hic$V4 %in% nonDEgenes),]
nondecgene.hic <- cgene.hic[which(cgene.hic$V4 %in% nonDEgenes),]

sum(dehgene.hic$V10==0)
[1] 1402
sum(nondehgene.hic$V10==0)
[1] 6367
quantile(abs(dehgene.hic$V10), probs=seq(0, 1, 0.025))
         0%        2.5%          5%        7.5%         10%       12.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        15%       17.5%         20%       22.5%         25%       27.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        30%       32.5%         35%       37.5%         40%       42.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        45%       47.5%         50%       52.5%         55%       57.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        60%       62.5%         65%       67.5%         70%       72.5% 
      0.000       0.000       0.000     142.375    1302.000    2540.750 
        75%       77.5%         80%       82.5%         85%       87.5% 
   3770.750    5512.875    7596.000   11152.750   16301.000   21797.625 
        90%       92.5%         95%       97.5%        100% 
  31613.500   46132.250   67401.250  131755.375 5837313.000 
quantile(abs(nondehgene.hic$V10), probs=seq(0, 1, 0.025))
         0%        2.5%          5%        7.5%         10%       12.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        15%       17.5%         20%       22.5%         25%       27.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        30%       32.5%         35%       37.5%         40%       42.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        45%       47.5%         50%       52.5%         55%       57.5% 
      0.000       0.000       0.000       0.000       0.000       0.000 
        60%       62.5%         65%       67.5%         70%       72.5% 
      0.000       0.000       0.000       0.000       0.000     781.900 
        75%       77.5%         80%       82.5%         85%       87.5% 
   2000.000    3054.650    4423.400    6403.575    9956.100   15363.875 
        90%       92.5%         95%       97.5%        100% 
  23179.700   34837.575   54701.300  103895.750 6845725.000 

And we can see that the majority of the genes (57.5%) have direct overlap with a bin. I’ll thus start with one very conservative set with only genes that have direct overlap with a bin. Later I may return to this and add and another slightly more lenient bin capturing ~10% more of the genes by allowing +/- 5kb of wiggle room.

Linear Modeling Annotation

In this next section I simply add information obtained from linear modeling on the Hi-C interaction frequencies to the appropriate genes having overlap with Hi-C bins. Because one Hi-C bin frequently shows up many times in the data, this means I must choose some kind of summary for Hi-C contact frequencies and linear modeling annotations for each gene. I toy with a variety of these summaries here, including choosing the minimum FDR contact, the maximum beta contact, the upstream contact, or summarizing all a bin’s contacts with the weighted Z-combine method or median FDR values.

hgene.hic.overlap <- filter(hgene.hic, V10==0) #Still leaves a solid ~26k genes.
cgene.hic.overlap <- filter(cgene.hic, V10==0) #Still leaves a solid ~26k genes.

#Add a column to both dfs indicating where along a bin the gene in question is found (from 0-10k):
hgene.hic.overlap$bin_pos <- abs(hgene.hic.overlap$V8-hgene.hic.overlap$V2)
cgene.hic.overlap$bin_pos <- abs(cgene.hic.overlap$V8-cgene.hic.overlap$V2)

#Rearrange columns and create another column of the bin ID.
hgene.hic.overlap <- hgene.hic.overlap[,c(4, 7:9, 6, 11, 1:2)]
hgene.hic.overlap$HID <- paste(hgene.hic.overlap$V7, hgene.hic.overlap$V8, sep="-")
cgene.hic.overlap <- cgene.hic.overlap[,c(4, 7:9, 6, 11, 1:2)]
cgene.hic.overlap$CID <- paste(cgene.hic.overlap$V7, cgene.hic.overlap$V8, sep="-")
colnames(hgene.hic.overlap) <- c("genes", "HiC_chr", "H1start", "H1end", "Hstrand", "bin_pos", "genechr", "genepos", "HID")
colnames(cgene.hic.overlap) <- c("genes", "HiC_chr", "C1start", "C1end", "Cstrand", "bin_pos", "genechr", "genepos", "CID")
#Gets me an hfinal table with a lot of the information concatenated together--now need the same thing for chimps, only to get the n contacts (since this could differ!)
hbindf <- select(data.filtered, "H1", "H2", "ALLvar", "SE", "sp_beta", "sp_pval", "sp_BH_pval", "Hdist")
names(hbindf) <- c("HID", "HID2", "ALLvar", "SE", "sp_beta", "sp_pval", "sp_BH_pval", "distance") #I have confirmed that all the HID2s are higher numbered coordinates than the HID1s, the only instance in which this isn't the case is when the two bins are identical (this should have been filtered out long before now).

hbindf <- hbindf[(which(hbindf$dist!=0)),] #Removes pairs where the same bin represents both mates. These instances occur exclusively when liftOver of the genomic coordinates from one species to another, and the subsequent rounding to the nearest 10kb, results in a contact between adjacent bins in one species being mapped as a contact between the same bin in the other species. Because there are less than 50 instances of this total in the dataset I simply remove it here without further worry.

#Remembering that all the first mates in the pair are lower coordinates than the second mates:
#This works for getting the FDR of closest downstream hits for the first column. Technically this would also make these the closest upstream hits for any bins that are UNIQUE and NOT REPEATED to the second column. For unique bins in this column, they have no upstream hits, and this gets their downstream hits. I can do the same thing but on the second set of IDs to get the potential upstream hits for any bins, then do a full_join on the two to get everything! Many of these metrics need to be done on a duplicated df to ensure I have all copies of a bin in one column, but the upstream and downstream analyses need to be run separately.
group_by(hbindf, HID) %>% summarise(DS_bin=HID2[which.min(distance)], DS_FDR=sp_BH_pval[which.min(distance)], DS_dist=distance[which.min(distance)]) -> hbin1.downstream

group_by(hbindf, HID2) %>% summarise(US_bin=HID[which.min(distance)], US_FDR=sp_BH_pval[which.min(distance)], US_dist=distance[which.min(distance)]) -> hbin2.upstream
colnames(hbin2.upstream) <- c("HID", "US_bin", "US_FDR", "US_dist")

Hstreams <- full_join(hbin1.downstream, hbin2.upstream, by="HID")

#Now, need to create a df with all the hits duplicated (but columns reversed) to account for duplicated bins in each column. This is better for any analysis that shares information across the interactions (minimums, sums, means, medians, etc.)
hbindf.flip <- hbindf[,c(2, 1, 3:7)]
colnames(hbindf.flip)[1:2] <- c("HID", "HID2")
hbindf_x2 <- rbind(hbindf[,1:7], hbindf.flip) #It's worth noting that a version of this with duplicates removed would be very useful for enrichment analyses...

#Now, use group_by from dplyr to combine information for a given bin across all its Hi-C contacts. Here I'll be pulling out contact, p-value, and bin with minimum FDR, its beta; the median FDR; the maximum beta and its FDR and bin; and a weighted combination method for p-values for species from linear modeling. This is based off of (http://onlinelibrary.wiley.com/doi/10.1111/j.1420-9101.2005.00917.x/full) under the assumption $s2.post is the actual error variance. (forthcoming)
group_by(hbindf_x2, HID) %>% summarise(min_FDR_bin=HID2[which.min(sp_BH_pval)], min_FDR=min(sp_BH_pval), min_FDR_pval=sp_pval[which.min(sp_BH_pval)], min_FDR_B=sp_beta[which.min(sp_BH_pval)], median_FDR=median(sp_BH_pval),  weighted_Z.ALLvar=pnorm((sum((1/ALLvar)*((qnorm(1-sp_pval))))/sqrt(sum((1/ALLvar)^2))), lower.tail=FALSE), weighted_Z.s2post=pnorm(sum((1/(SE^2))*qnorm(1-sp_pval))/sqrt(sum(1/SE^2)), lower.tail=FALSE), fisher=-2*sum(log(sp_pval)), numcontacts=n(), max_B_bin=HID2[which.max(abs(sp_beta))], max_B_FDR=sp_BH_pval[which.max(abs(sp_beta))], max_B=sp_beta[which.max(abs(sp_beta))]) -> hbin.info

#Now, full_join the hbin.info and Hstreams dfs, incorporating all the information about the hbins in my data:
full_join(hbin.info, Hstreams, by="HID") -> hbin.full.info

#Now I combine the gene overlap tables and the full information tables for the human genes and bins!
left_join(hgene.hic.overlap, hbin.full.info, by="HID") -> humgenes.hic.full
colnames(humgenes.hic.full)[1:5] <- c("genes", "Hchr", "Hstart", "Hend", "Hstrand") #Fix column names for what was just created

###Now, do the whole thing over again for chimps, and then combine with the human gene overlap before joining on detable!
#Gets me a cfinal table with a lot of the information concatenated together.
cbindf <- select(data.filtered, "C1", "C2", "ALLvar", "SE", "sp_beta", "sp_pval", "sp_BH_pval", "Cdist") #Pulling out cols C1, C2, ALLvar, SE, sp_beta, sp_pval, sp_BH_pval, and Cdist
names(cbindf) <- c("CID", "CID2", "ALLvar", "SE", "sp_beta", "sp_pval", "sp_BH_pval", "distance") #I have confirmed that all the CID2s are higher numbered coordinates than the CID1s, the only instance in which this isn't the case is when the two bins are identical (this should have been filtered out long before now).

cbindf <- cbindf[(which(cbindf$dist!=0)),] #Removes rows from the cbindf that REALLY shouldn't be there to begin with. There are ~620 hits like this.

#Remembering that all the first mates in the pair are lower coordinates than the second mates:
#This works for getting the FDR of closest downstream hits for the first column. Technically this would also make these the closest upstream hits for any bins that are UNIQUE and NOT REPEATED to the second column. For unique bins in this column, they have no upstream hits, and this gets their downstream hits. I can do the same thing but on the second set of IDs to get the potential upstream hits for any bins, then do a full_join on the two to get everything! Many of these metrics need to be done on a duplicated df to ensure I have all copies of a bin in one column, but the upstream and downstream analyses need to be run separately.
group_by(cbindf, CID) %>% summarise(DS_bin=CID2[which.min(distance)], DS_FDR=sp_BH_pval[which.min(distance)], DS_dist=distance[which.min(distance)]) -> cbin1.downstream

group_by(cbindf, CID2) %>% summarise(US_bin=CID[which.min(distance)], US_FDR=sp_BH_pval[which.min(distance)], US_dist=distance[which.min(distance)]) -> cbin2.upstream
colnames(cbin2.upstream) <- c("CID", "US_bin", "US_FDR", "US_dist")

Cstreams <- full_join(cbin1.downstream, cbin2.upstream, by="CID")

#Now, need to create a df with all the hits duplicated (but columns reversed) to account for duplicated bins in each column. This is better for any analysis that shares information across the interactions (minimums, sums, means, medians, etc.)
cbindf.flip <- cbindf[,c(2, 1, 3:7)]
colnames(cbindf.flip)[1:2] <- c("CID", "CID2")
cbindf_x2 <- rbind(cbindf[,1:7], cbindf.flip)

#Group by again for chimp hits as was done for humans above.
group_by(cbindf_x2, CID) %>% summarise(min_FDR_bin=CID2[which.min(sp_BH_pval)], min_FDR=min(sp_BH_pval), min_FDR_B=sp_beta[which.min(sp_BH_pval)], median_FDR=median(sp_BH_pval), weighted_Z.ALLvar=pnorm((sum((1/ALLvar)*((qnorm(1-sp_pval))))/sqrt(sum((1/ALLvar)^2))), lower.tail=FALSE), weighted_Z.s2post=pnorm(sum((1/(SE^2))*qnorm(1-sp_pval))/sqrt(sum(1/SE^2)), lower.tail=FALSE), fisher=-2*sum(log(sp_pval)), numcontacts=n(), max_B_bin=CID2[which.max(abs(sp_beta))], max_B_FDR=sp_BH_pval[which.max(abs(sp_beta))], max_B=sp_beta[which.max(abs(sp_beta))]) -> cbin.info

#Now, full_join the cbin.info and Cstreams dfs, incorporating all the information about the cbins in my data:
full_join(cbin.info, Cstreams, by="CID") -> cbin.full.info

#Now I combine the gene overlap tables and the full information tables for the human genes and bins!
left_join(cgene.hic.overlap, cbin.full.info, by="CID") -> chimpgenes.hic.full
colnames(chimpgenes.hic.full)[1:5] <- c("genes", "Hchr", "Hstart", "Hend", "Hstrand") #Fix column names for what was just created

#Now, combine chimpgenes.hic.full and humgenes.hic.full before a final left_join on detable:
full_join(humgenes.hic.full, chimpgenes.hic.full, by="genes", suffix=c(".H", ".C")) -> genes.hic.info
left_join(detable, genes.hic.info, by="genes") -> gene.hic.overlap.info

#Clean this dataframe up, removing rows where there is absolutely no Hi-C information for the gene.
filt.indices <- rowSums(is.na(gene.hic.overlap.info)) #51 NA values are found when there is absolutely no Hi-C information.
filt.indices <- which(filt.indices==51)
gene.hic.filt <- gene.hic.overlap.info[-filt.indices,] #Still leaves a solid 8,174 genes. Note that I will have to choose human or chimp values here for many of these columns, as not all of the values are the same (and many are missing in one species relative to the other). In some cases, may be able to just take minimum or maximum value from either in order to get at what I want.
saveRDS(gene.hic.filt, "output/gene.hic.filt.RDS")

Differential Expression-Differential Hi-C Enrichment Analyses

Now I look for enrichment of DHi-C in DE genes using a variety of different metrics to call DHi-C. I now look to see if genes that are differentially expressed are also differential in Hi-C contacts (DHi-C). That is to say, are differentially expressed genes enriched in their overlapping bins for Hi-C contacts that are also differential between the species? To do this I utilize p-values from my prior linear modeling as well as previous RNA-seq analysis. I construct a function to calculate proportions of DE and DHi-C genes, as well as a function to plot this out in a variety of different ways.

####Enrichment analyses!
#A function for calculating proportion of DE genes that are DHi-C under a variety of different paradigms. Accounts for when no genes are DHi-C and when all genes are DHi-C. Returns the proportion of DE genes that are also DHi-C, as well as the expected proportion based on conditional probability alone.
prop.calculator <- function(de.vec, hic.vec, i, k){
  my.result <- data.frame(prop=NA, exp.prop=NA, chisq.p=NA, Dneither=NA, DE=NA, DHiC=NA, Dboth=NA)
  bad.indices <- which(is.na(hic.vec)) #First obtain indices where Hi-C info is missing, if there are any, then remove from both vectors.
  if(length(bad.indices>0)){
  de.vec <- de.vec[-bad.indices]
  hic.vec <- hic.vec[-bad.indices]}
  de.vec <- ifelse(de.vec<=i, 1, 0)
  hic.vec <- ifelse(hic.vec<=k, 1, 0)
  if(sum(hic.vec, na.rm=TRUE)==0){#The case where no genes show up as DHi-C.
    my.result[1,] <- c(0, 0, 0, sum(de.vec==0, na.rm=TRUE), sum(de.vec==1, na.rm=TRUE), 0, 0) #Since no genes are DHi-C, the proportion is 0 and our expectation is 0, set p-val=0 since it's irrelevant.
  }
  else if(sum(hic.vec)==length(hic.vec)){ #The case where every gene shows up as DHi-C
    my.result[1,] <- c(1, 1, 0, 0, 0, sum(hic.vec==1&de.vec==0, na.rm = TRUE), sum(de.vec==1&hic.vec==1, na.rm=TRUE)) #If every gene is DHi-C, the observed proportion of DE genes DHi-C is 1, and the expected proportion of DE genes also DHi-C would also be 1 (all DE genes are DHi-C, since all genes are). Again set p-val to 0 since irrelevant comparison.
  }
  else{#The typical case, where we get an actual table
    mytable <- table(as.data.frame(cbind(de.vec, hic.vec)))
    my.result[1,1] <- mytable[2,2]/sum(mytable[2,]) #The observed proportion of DE genes that are also DHi-C. # that are both/total # DE
    my.result[1,2] <- (((sum(mytable[2,])/sum(mytable))*((sum(mytable[,2])/sum(mytable))))*sum(mytable))/sum(mytable[2,]) #The expected proportion: (p(DE) * p(DHiC)) * total # genes / # DE genes
    my.result[1,3] <- chisq.test(mytable)$p.value
    my.result[1,4] <- mytable[1,1]
    my.result[1,5] <- mytable[2,1]
    my.result[1,6] <- mytable[1,2]
    my.result[1,7] <- mytable[2,2]
  }
  return(my.result)
}

#This is a function that computes observed and expected proportions of DE and DHiC enrichments,  and spits out a variety of different visualizations for them. As input it takes a dataframe, the names of its DHiC and DE p-value columns, and a name to represent the type of Hi-C contact summary for the gene that ends up on the x-axis of all the plots.
enrichment.plotter <- function(df, HiC_col, DE_col, xlab, xmax=0.3, i=c(0.01, 0.025, 0.05, 0.075, 0.1), k=seq(0.01, 1, 0.01), recip=F){
  enrich.table <- data.frame(DEFDR = c(rep(i[1], 100), rep(i[2], 100), rep(i[3], 100), rep(i[4], 100), rep(i[5], 100)), DHICFDR=rep(k, 5), prop.obs=NA, prop.exp=NA, chisq.p=NA, Dneither=NA, DE=NA, DHiC=NA, Dboth=NA)
  for(de.FDR in i){
    for(hic.FDR in k){
      enrich.table[which(enrich.table$DEFDR==de.FDR&enrich.table$DHICFDR==hic.FDR), 3:9] <- prop.calculator(df[,DE_col], df[,HiC_col], de.FDR, hic.FDR)
    }
  }
  des.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=prop.obs, group=as.factor(DEFDR), color=as.factor(DEFDR))) +geom_line()+ geom_line(aes(y=prop.exp), linetype="dashed", size=0.5) + ggtitle("Enrichment of DC in DE Genes") + xlab(xlab) + ylab("Proportion of DE genes that are DC") + guides(color=guide_legend(title="FDR for DE Genes"))
  dhics.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dboth+DHiC), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + geom_line(aes(y=(((((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth)))*(Dneither+DE+DHiC+Dboth))/(DHiC+Dboth))), linetype="dashed") + ylab("Proportion of DC genes that are DE") +xlab(xlab) + ggtitle("Enrichment of DE in DC Genes") + coord_cartesian(xlim=c(0, xmax)) + guides(color=guide_legend(title="DE FDR"))
  joint.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dneither+DE+DHiC+Dboth), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + ylab("Proportion of ALL Genes both DE & DHi-C") + xlab(xlab) + geom_line(aes(y=((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth))), linetype="dashed") + ggtitle("Enrichment of Joint DE & DHi-C in All Genes")
  chisq.p <- ggplot(data=enrich.table, aes(x=DHICFDR, y=-log10(chisq.p), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_point() + geom_hline(yintercept=-log10(0.05), color="red") + ggtitle("Chi-squared Test P-values for Enrichment of DC in DE Genes") + xlab(xlab) + ylab("-log10(chi-squared p-values)") + coord_cartesian(xlim=c(0, xmax)) + guides(color=guide_legend(title="DE FDR"))
  if(recip==TRUE){
      des.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=prop.obs, group=as.factor(DEFDR), color=as.factor(DEFDR))) +geom_line()+ geom_line(aes(y=prop.exp), linetype="dashed", size=0.5) + ggtitle("Enrichment of DE in DC Genes") + xlab(xlab) + ylab("Proportion of DC genes that are DE") + guides(color=guide_legend(title="FDR for DC Genes"))
  dhics.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dboth+DHiC), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + geom_line(aes(y=(((((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth)))*(Dneither+DE+DHiC+Dboth))/(DHiC+Dboth))), linetype="dashed") + ylab("Proportion of DE genes that are DC") +xlab(xlab) + ggtitle("Enrichment of DC in DE Genes") + coord_cartesian(xlim=c(0, xmax)) + guides(color=guide_legend(title="DC FDR"))
  joint.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dneither+DE+DHiC+Dboth), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + ylab("Proportion of ALL Genes both DE & DHi-C") + xlab(xlab) + geom_line(aes(y=((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth))), linetype="dashed") + ggtitle("Enrichment of Joint DE & DHi-C in All Genes")
  chisq.p <- ggplot(data=enrich.table, aes(x=DHICFDR, y=-log10(chisq.p), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_point() + geom_hline(yintercept=-log10(0.05), color="red") + ggtitle("Chi-squared Test P-values for Enrichment of DE in DC Genes") + xlab(xlab) + ylab("-log10(chi-squared p-values)") + coord_cartesian(xlim=c(0, xmax)) + guides(color=guide_legend(title="DC FDR"))
  }
  print(des.enriched)
  print(dhics.enriched)
  print(joint.enriched)
  print(chisq.p)
  print(enrich.table)#[which(enrich.table$DEFDR==0.1),]) #Added to figure out comparison for the paper.
}

#Visualization of enrichment of DE/DC in one another. For most of these, using the gene.hic.filt df is sufficient as their Hi-C FDR numbers are the same. For the upstream genes it's a little more complicated because gene.hic.filt doesn't incorporate strand information on the genes, so use the specific US dfs for that, with the USFDR column.
#FIG6
enrichment.plotter(gene.hic.filt, "min_FDR.H", "adj.P.Val", "Minimum FDR of Hi-C Contacts Overlapping Gene", xmax=1) #FIG6A/B
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp    chisq.p Dneither   DE DHiC
1   0.010    0.01 0.04255319 0.04598145 0.80065262     6957  450  337
2   0.010    0.02 0.05531915 0.05963421 0.75877770     6857  444  437
3   0.010    0.03 0.06595745 0.06942298 0.83261502     6786  439  508
4   0.010    0.04 0.08723404 0.08037094 0.63327774     6711  429  583
5   0.010    0.05 0.09787234 0.09222050 0.72283415     6624  424  670
6   0.010    0.06 0.11276596 0.10419887 0.58278920     6538  417  756
7   0.010    0.07 0.13191489 0.11424523 0.24296869     6469  408  825
8   0.010    0.08 0.15319149 0.12660999 0.08609382     6383  398  911
9   0.010    0.09 0.16808511 0.14026275 0.08479409     6284  391 1010
10  0.010    0.10 0.18510638 0.15108192 0.03953562     6208  383 1086
11  0.010    0.11 0.19574468 0.16280268 0.05344168     6122  378 1172
12  0.010    0.12 0.20638298 0.17709943 0.09824852     6016  373 1278
13  0.010    0.13 0.21914894 0.18907779 0.09753188     5929  367 1365
14  0.010    0.14 0.23404255 0.20260175 0.09094805     5831  360 1463
15  0.010    0.15 0.25319149 0.21586811 0.04869491     5737  351 1557
16  0.010    0.16 0.26595745 0.22797527 0.04903338     5649  345 1645
17  0.010    0.17 0.28723404 0.24252962 0.02276395     5546  335 1748
18  0.010    0.18 0.30000000 0.25540958 0.02558375     5452  329 1842
19  0.010    0.19 0.31063830 0.27009274 0.04671135     5343  324 1951
20  0.010    0.20 0.33404255 0.28657908 0.02171933     5226  313 2068
21  0.010    0.21 0.34468085 0.29752705 0.02413636     5146  308 2148
22  0.010    0.22 0.36382979 0.31491499 0.02120831     5020  299 2274
23  0.010    0.23 0.38297872 0.32843895 0.01087114     4924  290 2370
24  0.010    0.24 0.39787234 0.34453890 0.01388704     4806  283 2488
25  0.010    0.25 0.40638298 0.36128284 0.04032397     4680  279 2614
26  0.010    0.26 0.42340426 0.37854199 0.04340600     4554  271 2740
27  0.010    0.27 0.43829787 0.39657393 0.06301265     4421  264 2873
28  0.010    0.28 0.45106383 0.41409067 0.10297024     4291  258 3003
29  0.010    0.29 0.45957447 0.42928903 0.18667669     4177  254 3117
30  0.010    0.30 0.47872340 0.44448738 0.13539529     4068  245 3226
31  0.010    0.31 0.49574468 0.46032973 0.12318869     3953  237 3341
32  0.010    0.32 0.50638298 0.47359608 0.15529178     3855  232 3439
33  0.010    0.33 0.52127660 0.49330242 0.22862114     3709  225 3585
34  0.010    0.34 0.53191489 0.50901597 0.32860267     3592  220 3702
35  0.010    0.35 0.54680851 0.52357032 0.32068358     3486  213 3808
36  0.010    0.36 0.55957447 0.53464709 0.28458022     3406  207 3888
37  0.010    0.37 0.57659574 0.55229263 0.29587452     3277  199 4017
38  0.010    0.38 0.58510638 0.57109737 0.55852360     3135  195 4159
39  0.010    0.39 0.60425532 0.58861412 0.50759008     3008  186 4286
40  0.010    0.40 0.62340426 0.60497166 0.42679569     2890  177 4404
41  0.010    0.41 0.63617021 0.61862442 0.44786720     2790  171 4504
42  0.010    0.42 0.65957447 0.63369397 0.24927971     2684  160 4610
43  0.010    0.43 0.66595745 0.64837713 0.43910651     2573  157 4721
44  0.010    0.44 0.68297872 0.66138588 0.33190722     2480  149 4814
45  0.010    0.45 0.70425532 0.67928903 0.25203249     2351  139 4943
46  0.010    0.46 0.70638298 0.69178259 0.51201850     2255  138 5039
47  0.010    0.47 0.72127660 0.70376095 0.42029215     2169  131 5125
48  0.010    0.48 0.72765957 0.71470891 0.55599688     2087  128 5207
49  0.010    0.49 0.74893617 0.72501288 0.25216518     2017  118 5277
50  0.010    0.50 0.75957447 0.73634724 0.26055053     1934  113 5360
51  0.010    0.51 0.77234043 0.74510562 0.17920816     1872  107 5422
52  0.010    0.52 0.78723404 0.75643998 0.12132559     1791  100 5503
53  0.010    0.53 0.80000000 0.76738794 0.09488613     1712   94 5582
54  0.010    0.54 0.80000000 0.77460072 0.19268893     1656   94 5638
55  0.010    0.55 0.80638298 0.78554869 0.28130408     1574   91 5720
56  0.010    0.56 0.81489362 0.79224626 0.23406830     1526   87 5768
57  0.010    0.57 0.82127660 0.79894384 0.23524188     1477   84 5817
58  0.010    0.58 0.83191489 0.80757342 0.18658093     1415   79 5879
59  0.010    0.59 0.83829787 0.81543019 0.20871901     1357   76 5937
60  0.010    0.60 0.84468085 0.82290057 0.22482961     1302   73 5992
61  0.010    0.61 0.84468085 0.82972694 0.40848811     1249   73 6045
62  0.010    0.62 0.85531915 0.83681092 0.29103305     1199   68 6095
63  0.010    0.63 0.85744681 0.84312210 0.41475289     1151   67 6143
64  0.010    0.64 0.86595745 0.84981968 0.34528784     1103   63 6191
65  0.010    0.65 0.86808511 0.85793405 0.56043576     1041   62 6253
66  0.010    0.66 0.87446809 0.86476043 0.57183797      991   59 6303
67  0.010    0.67 0.88297872 0.87107161 0.46923996      946   55 6348
68  0.010    0.68 0.88723404 0.87493560 0.44746542      918   53 6376
69  0.010    0.69 0.89148936 0.88060278 0.49804378      876   51 6418
70  0.010    0.70 0.90425532 0.88730036 0.26101231      830   45 6464
71  0.010    0.71 0.91063830 0.89167955 0.19778405      799   42 6495
72  0.010    0.72 0.91276596 0.89760433 0.29829145      754   41 6540
73  0.010    0.73 0.91276596 0.90069552 0.41041195      730   41 6564
74  0.010    0.74 0.91276596 0.90494590 0.60637991      697   41 6597
75  0.010    0.75 0.91489362 0.90868109 0.68931937      669   40 6625
76  0.010    0.76 0.92127660 0.91228748 0.53088677      644   37 6650
77  0.010    0.77 0.92340426 0.91834106 0.74392509      598   36 6696
78  0.010    0.78 0.93617021 0.92323545 0.31858392      566   30 6728
79  0.010    0.79 0.94042553 0.92658423 0.27318268      542   28 6752
80  0.010    0.80 0.94042553 0.93044822 0.43320979      512   28 6782
81  0.010    0.81 0.94468085 0.93379701 0.37702207      488   26 6806
82  0.010    0.82 0.95106383 0.93766100 0.25365094      461   23 6833
83  0.010    0.83 0.95319149 0.94268418 0.36350870      423   22 6871
84  0.010    0.84 0.95744681 0.94654817 0.32809305      395   20 6899
85  0.010    0.85 0.95957447 0.94938176 0.35162900      374   19 6920
86  0.010    0.86 0.96382979 0.95260175 0.28466184      351   17 6943
87  0.010    0.87 0.96595745 0.95646574 0.35559180      322   16 6972
88  0.010    0.88 0.96808511 0.95981453 0.41177892      297   15 6997
89  0.010    0.89 0.97021277 0.96277692 0.45153142      275   14 7019
90  0.010    0.90 0.97234043 0.96586811 0.50524322      252   13 7042
91  0.010    0.91 0.97234043 0.96857290 0.72888005      231   13 7063
92  0.010    0.92 0.97234043 0.97256569 1.00000000      200   13 7094
93  0.010    0.93 0.97872340 0.97617208 0.82731077      175   10 7119
94  0.010    0.94 0.98085106 0.97913447 0.91863894      153    9 7141
95  0.010    0.95 0.98936170 0.98196806 0.28734175      135    5 7159
96  0.010    0.96 0.99361702 0.98596084 0.21010339      106    3 7188
97  0.010    0.97 0.99574468 0.98969603 0.26955354       78    2 7216
98  0.010    0.98 0.99574468 0.99291602 0.63787646       53    2 7241
99  0.010    0.99 0.99787234 0.99639361 0.87697095       27    1 7267
100 0.010    1.00 1.00000000 1.00000000 0.00000000        0    0 7294
101 0.025    0.01 0.04008667 0.04598145 0.40811699     6521  886  320
102 0.025    0.02 0.05417118 0.05963421 0.50118987     6428  873  413
103 0.025    0.03 0.06175515 0.06942298 0.36418385     6359  866  482
104 0.025    0.04 0.07908992 0.08037094 0.92986540     6290  850  551
105 0.025    0.05 0.09100758 0.09222050 0.94014921     6209  839  632
106 0.025    0.06 0.10617551 0.10419887 0.87917713     6130  825  711
107 0.025    0.07 0.12351029 0.11424523 0.37478472     6068  809  773
108 0.025    0.08 0.14301192 0.12660999 0.12266812     5990  791  851
109 0.025    0.09 0.15817985 0.14026275 0.10535314     5898  777  943
110 0.025    0.10 0.17118093 0.15108192 0.07714846     5826  765 1015
111 0.025    0.11 0.18093174 0.16280268 0.12311221     5744  756 1097
112 0.025    0.12 0.19284940 0.17709943 0.19726588     5644  745 1197
113 0.025    0.13 0.20368364 0.18907779 0.24503897     5561  735 1280
114 0.025    0.14 0.21776815 0.20260175 0.23894176     5469  722 1372
115 0.025    0.15 0.23076923 0.21586811 0.25863722     5378  710 1463
116 0.025    0.16 0.24268689 0.22797527 0.27431510     5295  699 1546
117 0.025    0.17 0.26002167 0.24252962 0.20055876     5198  683 1643
118 0.025    0.18 0.27735645 0.25540958 0.11214225     5114  667 1727
119 0.025    0.19 0.28927411 0.27009274 0.17423383     5011  656 1830
120 0.025    0.20 0.30552546 0.28657908 0.18770567     4898  641 1943
121 0.025    0.21 0.31310943 0.29752705 0.28696110     4820  634 2021
122 0.025    0.22 0.32719393 0.31491499 0.41343550     4698  621 2143
123 0.025    0.23 0.33911159 0.32843895 0.48506892     4604  610 2237
124 0.025    0.24 0.35427952 0.34453890 0.53098069     4493  596 2348
125 0.025    0.25 0.36511376 0.36128284 0.82461460     4373  586 2468
126 0.025    0.26 0.38244854 0.37854199 0.82234069     4255  570 2586
127 0.025    0.27 0.39761647 0.39657393 0.97356639     4129  556 2712
128 0.025    0.28 0.40953413 0.41409067 0.79192756     4004  545 2837
129 0.025    0.29 0.42036836 0.42928903 0.58376998     3896  535 2945
130 0.025    0.30 0.44203684 0.44448738 0.90105437     3798  515 3043
131 0.025    0.31 0.46262189 0.46032973 0.90950188     3694  496 3147
132 0.025    0.32 0.47128927 0.47359608 0.90890753     3599  488 3242
133 0.025    0.33 0.49079090 0.49330242 0.89852910     3464  470 3377
134 0.025    0.34 0.50379198 0.50901597 0.76178410     3354  458 3487
135 0.025    0.35 0.51895991 0.52357032 0.79203805     3255  444 3586
136 0.025    0.36 0.53087757 0.53464709 0.83410230     3180  433 3661
137 0.025    0.37 0.54929577 0.55229263 0.87303785     3060  416 3781
138 0.025    0.38 0.56446371 0.57109737 0.69034430     2928  402 3913
139 0.025    0.39 0.58396533 0.58861412 0.78705856     2810  384 4031
140 0.025    0.40 0.59913326 0.60497166 0.72583096     2697  370 4144
141 0.025    0.41 0.61105092 0.61862442 0.63938850     2602  359 4239
142 0.025    0.42 0.63271939 0.63369397 0.97680174     2505  339 4336
143 0.025    0.43 0.64572048 0.64837713 0.88600567     2403  327 4438
144 0.025    0.44 0.66088841 0.66138588 1.00000000     2316  313 4525
145 0.025    0.45 0.67605634 0.67928903 0.85197499     2191  299 4650
146 0.025    0.46 0.68147346 0.69178259 0.49358312     2099  294 4742
147 0.025    0.47 0.69339112 0.70376095 0.48601593     2017  283 4824
148 0.025    0.48 0.70422535 0.71470891 0.47609690     1942  273 4899
149 0.025    0.49 0.71722644 0.72501288 0.59948415     1874  261 4967
150 0.025    0.50 0.73239437 0.73634724 0.80214655     1800  247 5041
151 0.025    0.51 0.74214518 0.74510562 0.85744227     1741  238 5100
152 0.025    0.52 0.75406284 0.75643998 0.88992554     1664  227 5177
153 0.025    0.53 0.76381365 0.76738794 0.81629526     1588  218 5253
154 0.025    0.54 0.76923077 0.77460072 0.70841336     1537  213 5304
155 0.025    0.55 0.77898158 0.78554869 0.63468979     1461  204 5380
156 0.025    0.56 0.78331528 0.79224626 0.50332084     1413  200 5428
157 0.025    0.57 0.78873239 0.79894384 0.43487585     1366  195 5475
158 0.025    0.58 0.79523294 0.80757342 0.33268639     1305  189 5536
159 0.025    0.59 0.80390033 0.81543019 0.35929147     1252  181 5589
160 0.025    0.60 0.81798483 0.82290057 0.71075923     1207  168 5634
161 0.025    0.61 0.82015168 0.82972694 0.43665107     1156  166 5685
162 0.025    0.62 0.82990249 0.83681092 0.57710222     1110  157 5731
163 0.025    0.63 0.83423619 0.84312210 0.45773667     1065  153 5776
164 0.025    0.64 0.84182015 0.84981968 0.49925907     1020  146 5821
165 0.025    0.65 0.84723727 0.85793405 0.34647690      962  141 5879
166 0.025    0.66 0.85482124 0.86476043 0.37378970      916  134 5925
167 0.025    0.67 0.86132178 0.87107161 0.37383585      873  128 5968
168 0.025    0.68 0.86782232 0.87493560 0.52023651      849  122 5992
169 0.025    0.69 0.87757313 0.88060278 0.80387588      814  113 6027
170 0.025    0.70 0.89274106 0.88730036 0.61608201      776   99 6065
171 0.025    0.71 0.89815818 0.89167955 0.53639052      747   94 6094
172 0.025    0.72 0.90249187 0.89760433 0.64268159      705   90 6136
173 0.025    0.73 0.90465872 0.90069552 0.71117663      683   88 6158
174 0.025    0.74 0.90790899 0.90494590 0.78930904      653   85 6188
175 0.025    0.75 0.91007584 0.90868109 0.92364448      626   83 6215
176 0.025    0.76 0.91549296 0.91228748 0.76053550      603   78 6238
177 0.025    0.77 0.91982665 0.91834106 0.91117477      560   74 6281
178 0.025    0.78 0.92957746 0.92323545 0.48070001      531   65 6310
179 0.025    0.79 0.93174431 0.92658423 0.56657290      507   63 6334
180 0.025    0.80 0.93174431 0.93044822 0.92353792      477   63 6364
181 0.025    0.81 0.93499458 0.93379701 0.93196347      454   60 6387
182 0.025    0.82 0.93824485 0.93766100 0.99549869      427   57 6414
183 0.025    0.83 0.94257855 0.94268418 1.00000000      392   53 6449
184 0.025    0.84 0.94907909 0.94654817 0.77470398      368   47 6473
185 0.025    0.85 0.95449621 0.94938176 0.49959474      351   42 6490
186 0.025    0.86 0.95882990 0.95260175 0.38641419      330   38 6511
187 0.025    0.87 0.95991333 0.95646574 0.64486750      301   37 6540
188 0.025    0.88 0.96316360 0.95981453 0.64361478      278   34 6563
189 0.025    0.89 0.96749729 0.96277692 0.47496923      259   30 6582
190 0.025    0.90 0.97074756 0.96586811 0.43938661      238   27 6603
191 0.025    0.91 0.97291441 0.96857290 0.48087407      219   25 6622
192 0.025    0.92 0.97399783 0.97256569 0.85995410      189   24 6652
193 0.025    0.93 0.97724810 0.97617208 0.90972118      164   21 6677
194 0.025    0.94 0.97941495 0.97913447 1.00000000      143   19 6698
195 0.025    0.95 0.98591549 0.98196806 0.40746218      127   13 6714
196 0.025    0.96 0.99241603 0.98596084 0.10378570      102    7 6739
197 0.025    0.97 0.99458288 0.98969603 0.16373325       75    5 6766
198 0.025    0.98 0.99674973 0.99291602 0.20393425       52    3 6789
199 0.025    0.99 0.99783315 0.99639361 0.62784727       26    2 6815
200 0.025    1.00 1.00000000 1.00000000 0.00000000        0    0 6841
201 0.050    0.01 0.04568166 0.04598145 1.00000000     6070 1337  293
202 0.050    0.02 0.05852962 0.05963421 0.89613487     5982 1319  381
203 0.050    0.03 0.06566738 0.06942298 0.58035757     5916 1309  447
204 0.050    0.04 0.08065667 0.08037094 1.00000000     5852 1288  511
205 0.050    0.05 0.09279086 0.09222050 0.97566462     5777 1271  586
206 0.050    0.06 0.10635261 0.10419887 0.80787562     5703 1252  660
207 0.050    0.07 0.11848680 0.11424523 0.61362569     5642 1235  721
208 0.050    0.08 0.13490364 0.12660999 0.32373319     5569 1212  794
209 0.050    0.09 0.15060671 0.14026275 0.23440403     5485 1190  878
210 0.050    0.10 0.16345468 0.15108192 0.16537309     5419 1172  944
211 0.050    0.11 0.17344754 0.16280268 0.24925195     5342 1158 1021
212 0.050    0.12 0.18629550 0.17709943 0.33840182     5249 1140 1114
213 0.050    0.13 0.19486081 0.18907779 0.56668342     5168 1128 1195
214 0.050    0.14 0.21056388 0.20260175 0.43402620     5085 1106 1278
215 0.050    0.15 0.22412562 0.21586811 0.42721337     5001 1087 1362
216 0.050    0.16 0.23768737 0.22797527 0.35653532     4926 1068 1437
217 0.050    0.17 0.25410421 0.24252962 0.27920583     4836 1045 1527
218 0.050    0.18 0.27194861 0.25540958 0.12497397     4761 1020 1602
219 0.050    0.19 0.28551035 0.27009274 0.16078178     4666 1001 1697
220 0.050    0.20 0.30121342 0.28657908 0.19171301     4560  979 1803
221 0.050    0.21 0.30835118 0.29752705 0.34382198     4485  969 1878
222 0.050    0.22 0.32762313 0.31491499 0.27157485     4377  942 1986
223 0.050    0.23 0.33904354 0.32843895 0.36696772     4288  926 2075
224 0.050    0.24 0.35760171 0.34453890 0.26895853     4189  900 2174
225 0.050    0.25 0.37330478 0.36128284 0.31537213     4081  878 2282
226 0.050    0.26 0.38758030 0.37854199 0.45927192     3967  858 2396
227 0.050    0.27 0.39900071 0.39657393 0.86112174     3843  842 2520
228 0.050    0.28 0.41827266 0.41409067 0.74815121     3734  815 2629
229 0.050    0.29 0.43040685 0.42928903 0.94931904     3633  798 2730
230 0.050    0.30 0.44825125 0.44448738 0.77680801     3540  773 2823
231 0.050    0.31 0.46966453 0.46032973 0.45642611     3447  743 2916
232 0.050    0.32 0.47822984 0.47359608 0.72322318     3356  731 3007
233 0.050    0.33 0.50035689 0.49330242 0.57965926     3234  700 3129
234 0.050    0.34 0.51391863 0.50901597 0.70694834     3131  681 3232
235 0.050    0.35 0.52819415 0.52357032 0.72391458     3038  661 3325
236 0.050    0.36 0.53818701 0.53464709 0.79190019     2966  647 3397
237 0.050    0.37 0.55674518 0.55229263 0.73344693     2855  621 3508
238 0.050    0.38 0.57316203 0.57109737 0.88655280     2732  598 3631
239 0.050    0.39 0.59457530 0.58861412 0.63772497     2626  568 3737
240 0.050    0.40 0.60956460 0.60497166 0.72014169     2520  547 3843
241 0.050    0.41 0.62241256 0.61862442 0.77022959     2432  529 3931
242 0.050    0.42 0.64311206 0.63369397 0.43680629     2344  500 4019
243 0.050    0.43 0.65738758 0.64837713 0.45365779     2250  480 4113
244 0.050    0.44 0.67309065 0.66138588 0.32147178     2171  458 4192
245 0.050    0.45 0.68665239 0.67928903 0.53483031     2051  439 4312
246 0.050    0.46 0.69521770 0.69178259 0.78283632     1966  427 4397
247 0.050    0.47 0.70378301 0.70376095 1.00000000     1885  415 4478
248 0.050    0.48 0.71520343 0.71470891 0.98994577     1816  399 4547
249 0.050    0.49 0.72448251 0.72501288 0.98718344     1749  386 4614
250 0.050    0.50 0.73804425 0.73634724 0.89992756     1680  367 4683
251 0.050    0.51 0.74946467 0.74510562 0.70417062     1628  351 4735
252 0.050    0.52 0.76231263 0.75643998 0.59520524     1558  333 4805
253 0.050    0.53 0.77087794 0.76738794 0.75914192     1485  321 4878
254 0.050    0.54 0.77730193 0.77460072 0.81656117     1438  312 4925
255 0.050    0.55 0.78800857 0.78554869 0.83222827     1368  297 4995
256 0.050    0.56 0.79229122 0.79224626 1.00000000     1322  291 5041
257 0.050    0.57 0.79942898 0.79894384 0.98944418     1280  281 5083
258 0.050    0.58 0.80513919 0.80757342 0.82752345     1221  273 5142
259 0.050    0.59 0.81299072 0.81543019 0.82435119     1171  262 5192
260 0.050    0.60 0.82655246 0.82290057 0.72119219     1132  243 5231
261 0.050    0.61 0.82940757 0.82972694 1.00000000     1083  239 5280
262 0.050    0.62 0.83654532 0.83681092 1.00000000     1038  229 5325
263 0.050    0.63 0.84296931 0.84312210 1.00000000      998  220 5365
264 0.050    0.64 0.84939329 0.84981968 0.99358208      955  211 5408
265 0.050    0.65 0.85438972 0.85793405 0.70581196      899  204 5464
266 0.050    0.66 0.86009993 0.86476043 0.60284549      854  196 5509
267 0.050    0.67 0.86581014 0.87107161 0.54510780      813  188 5550
268 0.050    0.68 0.87009279 0.87493560 0.57500464      789  182 5574
269 0.050    0.69 0.87794433 0.88060278 0.76916088      756  171 5607
270 0.050    0.70 0.89150607 0.88730036 0.61480650      723  152 5640
271 0.050    0.71 0.89578872 0.89167955 0.61764433      695  146 5668
272 0.050    0.72 0.90149893 0.89760433 0.62947213      657  138 5706
273 0.050    0.73 0.90435403 0.90069552 0.64807227      637  134 5726
274 0.050    0.74 0.90935046 0.90494590 0.56826399      611  127 5752
275 0.050    0.75 0.91363312 0.90868109 0.50954684      588  121 5775
276 0.050    0.76 0.92005710 0.91228748 0.27860461      569  112 5794
277 0.050    0.77 0.92505353 0.91834106 0.33726522      529  105 5834
278 0.050    0.78 0.93290507 0.92323545 0.14808085      502   94 5861
279 0.050    0.79 0.93504640 0.92658423 0.19883546      479   91 5884
280 0.050    0.80 0.93504640 0.93044822 0.49061471      449   91 5914
281 0.050    0.81 0.93861527 0.93379701 0.45815911      428   86 5935
282 0.050    0.82 0.94075660 0.93766100 0.63953097      401   83 5962
283 0.050    0.83 0.94361171 0.94268418 0.91915308      366   79 5997
284 0.050    0.84 0.94932191 0.94654817 0.65686096      344   71 6019
285 0.050    0.85 0.95289079 0.94938176 0.55216778      327   66 6036
286 0.050    0.86 0.95717345 0.95260175 0.41215371      308   60 6055
287 0.050    0.87 0.96074233 0.95646574 0.42707530      283   55 6080
288 0.050    0.88 0.96431121 0.95981453 0.38346634      262   50 6101
289 0.050    0.89 0.96859386 0.96277692 0.23306475      245   44 6118
290 0.050    0.90 0.97216274 0.96586811 0.17633893      226   39 6137
291 0.050    0.91 0.97430407 0.96857290 0.20280542      208   36 6155
292 0.050    0.92 0.97715917 0.97256569 0.28355744      181   32 6182
293 0.050    0.93 0.98001428 0.97617208 0.34473181      157   28 6206
294 0.050    0.94 0.98144183 0.97913447 0.57261651      136   26 6227
295 0.050    0.95 0.98572448 0.98196806 0.29083850      120   20 6243
296 0.050    0.96 0.99072091 0.98596084 0.12177157       96   13 6267
297 0.050    0.97 0.99428979 0.98969603 0.08279488       72    8 6291
298 0.050    0.98 0.99643112 0.99291602 0.11948034       50    5 6313
299 0.050    0.99 0.99785867 0.99639361 0.44466456       25    3 6338
300 0.050    1.00 1.00000000 1.00000000 0.00000000        0    0 6363
301 0.075    0.01 0.04756512 0.04598145 0.76655394     5725 1682  273
302 0.075    0.02 0.05945640 0.05963421 1.00000000     5640 1661  358
303 0.075    0.03 0.06964892 0.06942298 1.00000000     5582 1643  416
304 0.075    0.04 0.08380521 0.08037094 0.57945916     5522 1618  476
305 0.075    0.05 0.09569649 0.09222050 0.59777206     5451 1597  547
306 0.075    0.06 0.10872027 0.10419887 0.50716075     5381 1574  617
307 0.075    0.07 0.12117780 0.11424523 0.31759539     5325 1552  673
308 0.075    0.08 0.13703284 0.12660999 0.14487265     5257 1524  741
309 0.075    0.09 0.15402039 0.14026275 0.06356583     5181 1494  817
310 0.075    0.10 0.16534541 0.15108192 0.06197958     5117 1474  881
311 0.075    0.11 0.17440544 0.16280268 0.14265886     5042 1458  956
312 0.075    0.12 0.18573046 0.17709943 0.29578516     4951 1438 1047
313 0.075    0.13 0.19365798 0.18907779 0.59980375     4872 1424 1126
314 0.075    0.14 0.20894677 0.20260175 0.47085968     4794 1397 1204
315 0.075    0.15 0.21970555 0.21586811 0.67957048     4710 1378 1288
316 0.075    0.16 0.23556059 0.22797527 0.40529500     4644 1350 1354
317 0.075    0.17 0.25198188 0.24252962 0.30639453     4560 1321 1438
318 0.075    0.18 0.26840317 0.25540958 0.16345706     4489 1292 1509
319 0.075    0.19 0.28369196 0.27009274 0.15159826     4402 1265 1596
320 0.075    0.20 0.29841450 0.28657908 0.22188162     4300 1239 1698
321 0.075    0.21 0.30747452 0.29752705 0.31215222     4231 1223 1767
322 0.075    0.22 0.32559456 0.31491499 0.28454489     4128 1191 1870
323 0.075    0.23 0.33918460 0.32843895 0.28681863     4047 1167 1951
324 0.075    0.24 0.35900340 0.34453890 0.15363991     3957 1132 2041
325 0.075    0.25 0.37315968 0.36128284 0.24852885     3852 1107 2146
326 0.075    0.26 0.38901472 0.37854199 0.31516051     3746 1079 2252
327 0.075    0.27 0.40430351 0.39657393 0.46673784     3633 1052 2365
328 0.075    0.28 0.42355606 0.41409067 0.37277095     3531 1018 2467
329 0.075    0.29 0.43827860 0.42928903 0.40035154     3439  992 2559
330 0.075    0.30 0.45413364 0.44448738 0.36763845     3349  964 2649
331 0.075    0.31 0.47281993 0.46032973 0.24160853     3259  931 2739
332 0.075    0.32 0.48131370 0.47359608 0.47652300     3171  916 2827
333 0.075    0.33 0.50396376 0.49330242 0.32095825     3058  876 2940
334 0.075    0.34 0.51925255 0.50901597 0.34112784     2963  849 3035
335 0.075    0.35 0.53284258 0.52357032 0.38949728     2874  825 3124
336 0.075    0.36 0.54416761 0.53464709 0.37591885     2808  805 3190
337 0.075    0.37 0.56342016 0.55229263 0.29708804     2705  771 3293
338 0.075    0.38 0.58097395 0.57109737 0.35404210     2590  740 3408
339 0.075    0.39 0.60079275 0.58861412 0.24776817     2489  705 3509
340 0.075    0.40 0.61608154 0.60497166 0.28964930     2389  678 3609
341 0.075    0.41 0.62740657 0.61862442 0.40282175     2303  658 3695
342 0.075    0.42 0.64496036 0.63369397 0.27573746     2217  627 3781
343 0.075    0.43 0.65911665 0.64837713 0.29507972     2128  602 3870
344 0.075    0.44 0.67667044 0.66138588 0.12961786     2058  571 3940
345 0.075    0.45 0.69309173 0.67928903 0.16608745     1948  542 4050
346 0.075    0.46 0.70328426 0.69178259 0.24539639     1869  524 4129
347 0.075    0.47 0.71291053 0.70376095 0.35318216     1793  507 4205
348 0.075    0.48 0.72593431 0.71470891 0.24661891     1731  484 4267
349 0.075    0.49 0.73612684 0.72501288 0.24614692     1669  466 4329
350 0.075    0.50 0.74858437 0.73634724 0.19457905     1603  444 4395
351 0.075    0.51 0.75821065 0.74510562 0.15951937     1552  427 4446
352 0.075    0.52 0.77123443 0.75643998 0.10600560     1487  404 4511
353 0.075    0.53 0.78029445 0.76738794 0.15314164     1418  388 4580
354 0.075    0.54 0.78652322 0.77460072 0.18291573     1373  377 4625
355 0.075    0.55 0.79728199 0.78554869 0.18226375     1307  358 4691
356 0.075    0.56 0.80124575 0.79224626 0.30431445     1262  351 4736
357 0.075    0.57 0.80747452 0.79894384 0.32517355     1221  340 4777
358 0.075    0.58 0.81540204 0.80757342 0.36010525     1168  326 4830
359 0.075    0.59 0.82276331 0.81543019 0.38492383     1120  313 4878
360 0.075    0.60 0.83465459 0.82290057 0.15081849     1083  292 4915
361 0.075    0.61 0.83861835 0.82972694 0.27352063     1037  285 4961
362 0.075    0.62 0.84484711 0.83681092 0.31580725      993  274 5005
363 0.075    0.63 0.85390713 0.84312210 0.16739312      960  258 5038
364 0.075    0.64 0.86013590 0.84981968 0.17934823      919  247 5079
365 0.075    0.65 0.86579841 0.85793405 0.29915267      866  237 5132
366 0.075    0.66 0.87089468 0.86476043 0.41333492      822  228 5176
367 0.075    0.67 0.87599094 0.87107161 0.50832477      782  219 5216
368 0.075    0.68 0.87938845 0.87493560 0.54672125      758  213 5240
369 0.075    0.69 0.88618347 0.88060278 0.43472590      726  201 5272
370 0.075    0.70 0.89750849 0.88730036 0.13345531      694  181 5304
371 0.075    0.71 0.90147225 0.89167955 0.14347446      667  174 5331
372 0.075    0.72 0.90600227 0.89760433 0.20062798      629  166 5369
373 0.075    0.73 0.90826727 0.90069552 0.24393075      609  162 5389
374 0.075    0.74 0.91336353 0.90494590 0.18481372      585  153 5413
375 0.075    0.75 0.91732729 0.90868109 0.16511240      563  146 5435
376 0.075    0.76 0.92298981 0.91228748 0.07822928      545  136 5453
377 0.075    0.77 0.92865232 0.91834106 0.07997020      508  126 5490
378 0.075    0.78 0.93544734 0.92323545 0.03216397      482  114 5516
379 0.075    0.79 0.93771234 0.92658423 0.04680648      460  110 5538
380 0.075    0.80 0.93771234 0.93044822 0.18950157      430  110 5568
381 0.075    0.81 0.94110985 0.93379701 0.17644415      410  104 5588
382 0.075    0.82 0.94337486 0.93766100 0.28283795      384  100 5614
383 0.075    0.83 0.94790487 0.94268418 0.30981514      353   92 5645
384 0.075    0.84 0.95300113 0.94654817 0.18970159      332   83 5666
385 0.075    0.85 0.95583239 0.94938176 0.17857730      315   78 5683
386 0.075    0.86 0.95922990 0.95260175 0.15338378      296   72 5702
387 0.075    0.87 0.96262741 0.95646574 0.16839440      272   66 5726
388 0.075    0.88 0.96545866 0.95981453 0.19184912      251   61 5747
389 0.075    0.89 0.96885617 0.96277692 0.14322828      234   55 5764
390 0.075    0.90 0.97225368 0.96586811 0.10806748      216   49 5782
391 0.075    0.91 0.97451869 0.96857290 0.12070896      199   45 5799
392 0.075    0.92 0.97734994 0.97256569 0.18767180      173   40 5825
393 0.075    0.93 0.98018120 0.97617208 0.24277593      150   35 5848
394 0.075    0.94 0.98131370 0.97913447 0.52591558      129   33 5869
395 0.075    0.95 0.98527746 0.98196806 0.27687700      114   26 5884
396 0.075    0.96 0.98980747 0.98596084 0.14757674       91   18 5907
397 0.075    0.97 0.99377123 0.98969603 0.07259162       69   11 5929
398 0.075    0.98 0.99546999 0.99291602 0.19546748       47    8 5951
399 0.075    0.99 0.99773499 0.99639361 0.39863476       24    4 5974
400 0.075    1.00 1.00000000 1.00000000 0.00000000        0    0 5998
401 0.100    0.01 0.04750480 0.04598145 0.74362827     5422 1985  258
402 0.100    0.02 0.05950096 0.05963421 1.00000000     5341 1960  339
403 0.100    0.03 0.07005758 0.06942298 0.93394914     5287 1938  393
404 0.100    0.04 0.08397313 0.08037094 0.50920578     5231 1909  449
405 0.100    0.05 0.09596929 0.09222050 0.51746272     5164 1884  516
406 0.100    0.06 0.10940499 0.10419887 0.38562990     5099 1856  581
407 0.100    0.07 0.12140115 0.11424523 0.24589844     5046 1831  634
408 0.100    0.08 0.13579655 0.12660999 0.15101717     4980 1801  700
409 0.100    0.09 0.15211132 0.14026275 0.07439011     4908 1767  772
410 0.100    0.10 0.16362764 0.15108192 0.06666100     4848 1743  832
411 0.100    0.11 0.17370441 0.16280268 0.12322944     4778 1722  902
412 0.100    0.12 0.18666027 0.17709943 0.19252438     4694 1695  986
413 0.100    0.13 0.19577735 0.18907779 0.37860379     4620 1676 1060
414 0.100    0.14 0.21065259 0.20260175 0.29964523     4546 1645 1134
415 0.100    0.15 0.22264875 0.21586811 0.39615701     4468 1620 1212
416 0.100    0.16 0.23800384 0.22797527 0.21301457     4406 1588 1274
417 0.100    0.17 0.25431862 0.24252962 0.15039611     4327 1554 1353
418 0.100    0.18 0.26871401 0.25540958 0.10983316     4257 1524 1423
419 0.100    0.19 0.28310940 0.27009274 0.12457637     4173 1494 1507
420 0.100    0.20 0.29846449 0.28657908 0.16925202     4077 1462 1603
421 0.100    0.21 0.30758157 0.29752705 0.25187428     4011 1443 1669
422 0.100    0.22 0.32581574 0.31491499 0.22057180     3914 1405 1766
423 0.100    0.23 0.34021113 0.32843895 0.19000146     3839 1375 1841
424 0.100    0.24 0.35844530 0.34453890 0.12480723     3752 1337 1928
425 0.100    0.25 0.37188100 0.36128284 0.24978701     3650 1309 2030
426 0.100    0.26 0.38819578 0.37854199 0.30024359     3550 1275 2130
427 0.100    0.27 0.40451056 0.39657393 0.40105072     3444 1241 2236
428 0.100    0.28 0.42274472 0.41409067 0.36191400     3346 1203 2334
429 0.100    0.29 0.43618042 0.42928903 0.47323849     3256 1175 2424
430 0.100    0.30 0.45201536 0.44448738 0.43374293     3171 1142 2509
431 0.100    0.31 0.47120921 0.46032973 0.25457326     3088 1102 2592
432 0.100    0.32 0.48176583 0.47359608 0.39663183     3007 1080 2673
433 0.100    0.33 0.50239923 0.49330242 0.34439699     2897 1037 2783
434 0.100    0.34 0.51631478 0.50901597 0.45107561     2804 1008 2876
435 0.100    0.35 0.53071017 0.52357032 0.46090827     2721  978 2959
436 0.100    0.36 0.54174664 0.53464709 0.46295164     2658  955 3022
437 0.100    0.37 0.55902111 0.55229263 0.48615317     2557  919 3123
438 0.100    0.38 0.57629559 0.57109737 0.59285329     2447  883 3233
439 0.100    0.39 0.59548944 0.58861412 0.47171659     2351  843 3329
440 0.100    0.40 0.61036468 0.60497166 0.57370348     2255  812 3425
441 0.100    0.41 0.62284069 0.61862442 0.66216216     2175  786 3505
442 0.100    0.42 0.63963532 0.63369397 0.52765148     2093  751 3587
443 0.100    0.43 0.65547025 0.64837713 0.44364507     2012  718 3668
444 0.100    0.44 0.67274472 0.66138588 0.20983956     1947  682 3733
445 0.100    0.45 0.68857965 0.67928903 0.30069640     1841  649 3839
446 0.100    0.46 0.69817658 0.69178259 0.47688419     1764  629 3916
447 0.100    0.47 0.70873321 0.70376095 0.58014657     1693  607 3987
448 0.100    0.48 0.72168906 0.71470891 0.42563783     1635  580 4045
449 0.100    0.49 0.73224568 0.72501288 0.40322193     1577  558 4103
450 0.100    0.50 0.74472169 0.73634724 0.32445052     1515  532 4165
451 0.100    0.51 0.75383877 0.74510562 0.29826415     1466  513 4214
452 0.100    0.52 0.76631478 0.75643998 0.23089924     1404  487 4276
453 0.100    0.53 0.77543186 0.76738794 0.32420678     1338  468 4342
454 0.100    0.54 0.78214971 0.77460072 0.35050652     1296  454 4384
455 0.100    0.55 0.79222649 0.78554869 0.40250175     1232  433 4448
456 0.100    0.56 0.79606526 0.79224626 0.63774733     1188  425 4492
457 0.100    0.57 0.80182342 0.79894384 0.72520014     1148  413 4532
458 0.100    0.58 0.80950096 0.80757342 0.81926469     1097  397 4583
459 0.100    0.59 0.81669866 0.81543019 0.88747250     1051  382 4629
460 0.100    0.60 0.82725528 0.82290057 0.56509889     1015  360 4665
461 0.100    0.61 0.83205374 0.82972694 0.76697930      972  350 4708
462 0.100    0.62 0.83973129 0.83681092 0.69865496      933  334 4747
463 0.100    0.63 0.84932821 0.84312210 0.38126656      904  314 4776
464 0.100    0.64 0.85508637 0.84981968 0.45265630      864  302 4816
465 0.100    0.65 0.86180422 0.85793405 0.57890477      815  288 4865
466 0.100    0.66 0.86756238 0.86476043 0.68926445      774  276 4906
467 0.100    0.67 0.87188100 0.87107161 0.92773530      734  267 4946
468 0.100    0.68 0.87619962 0.87493560 0.86875908      713  258 4967
469 0.100    0.69 0.88339731 0.88060278 0.67412835      684  243 4996
470 0.100    0.70 0.89299424 0.88730036 0.35730173      652  223 5028
471 0.100    0.71 0.89827255 0.89167955 0.27525344      629  212 5051
472 0.100    0.72 0.90211132 0.89760433 0.45252322      591  204 5089
473 0.100    0.73 0.90451056 0.90069552 0.52346083      572  199 5108
474 0.100    0.74 0.90930902 0.90494590 0.45305374      549  189 5131
475 0.100    0.75 0.91362764 0.90868109 0.38318171      529  180 5151
476 0.100    0.76 0.91890595 0.91228748 0.22878674      512  169 5168
477 0.100    0.77 0.92562380 0.91834106 0.16986108      479  155 5201
478 0.100    0.78 0.93234165 0.92323545 0.07547742      455  141 5225
479 0.100    0.79 0.93522073 0.92658423 0.08575394      435  135 5245
480 0.100    0.80 0.93570058 0.93044822 0.29296646      406  134 5274
481 0.100    0.81 0.94001919 0.93379701 0.19908756      389  125 5291
482 0.100    0.82 0.94289827 0.93766100 0.26994020      365  119 5315
483 0.100    0.83 0.94721689 0.94268418 0.32428996      335  110 5345
484 0.100    0.84 0.95249520 0.94654817 0.17567454      316   99 5364
485 0.100    0.85 0.95633397 0.94938176 0.10220986      302   91 5378
486 0.100    0.86 0.95921305 0.95260175 0.10952182      283   85 5397
487 0.100    0.87 0.96305182 0.95646574 0.09693741      261   77 5419
488 0.100    0.88 0.96545106 0.95981453 0.14248663      240   72 5440
489 0.100    0.89 0.96880998 0.96277692 0.10240876      224   65 5456
490 0.100    0.90 0.97216891 0.96586811 0.07481222      207   58 5473
491 0.100    0.91 0.97456814 0.96857290 0.07830098      191   53 5489
492 0.100    0.92 0.97696737 0.97256569 0.17388046      165   48 5515
493 0.100    0.93 0.97984645 0.97617208 0.22940229      143   42 5537
494 0.100    0.94 0.98080614 0.97913447 0.59290912      122   40 5558
495 0.100    0.95 0.98416507 0.98196806 0.43246647      107   33 5573
496 0.100    0.96 0.98992322 0.98596084 0.09128122       88   21 5592
497 0.100    0.97 0.99424184 0.98969603 0.02286025       68   12 5612
498 0.100    0.98 0.99568138 0.99291602 0.10801938       46    9 5634
499 0.100    0.99 0.99808061 0.99639361 0.19759913       24    4 5656
500 0.100    1.00 1.00000000 1.00000000 0.00000000        0    0 5680
    Dboth
1      20
2      26
3      31
4      41
5      46
6      53
7      62
8      72
9      79
10     87
11     92
12     97
13    103
14    110
15    119
16    125
17    135
18    141
19    146
20    157
21    162
22    171
23    180
24    187
25    191
26    199
27    206
28    212
29    216
30    225
31    233
32    238
33    245
34    250
35    257
36    263
37    271
38    275
39    284
40    293
41    299
42    310
43    313
44    321
45    331
46    332
47    339
48    342
49    352
50    357
51    363
52    370
53    376
54    376
55    379
56    383
57    386
58    391
59    394
60    397
61    397
62    402
63    403
64    407
65    408
66    411
67    415
68    417
69    419
70    425
71    428
72    429
73    429
74    429
75    430
76    433
77    434
78    440
79    442
80    442
81    444
82    447
83    448
84    450
85    451
86    453
87    454
88    455
89    456
90    457
91    457
92    457
93    460
94    461
95    465
96    467
97    468
98    468
99    469
100   470
101    37
102    50
103    57
104    73
105    84
106    98
107   114
108   132
109   146
110   158
111   167
112   178
113   188
114   201
115   213
116   224
117   240
118   256
119   267
120   282
121   289
122   302
123   313
124   327
125   337
126   353
127   367
128   378
129   388
130   408
131   427
132   435
133   453
134   465
135   479
136   490
137   507
138   521
139   539
140   553
141   564
142   584
143   596
144   610
145   624
146   629
147   640
148   650
149   662
150   676
151   685
152   696
153   705
154   710
155   719
156   723
157   728
158   734
159   742
160   755
161   757
162   766
163   770
164   777
165   782
166   789
167   795
168   801
169   810
170   824
171   829
172   833
173   835
174   838
175   840
176   845
177   849
178   858
179   860
180   860
181   863
182   866
183   870
184   876
185   881
186   885
187   886
188   889
189   893
190   896
191   898
192   899
193   902
194   904
195   910
196   916
197   918
198   920
199   921
200   923
201    64
202    82
203    92
204   113
205   130
206   149
207   166
208   189
209   211
210   229
211   243
212   261
213   273
214   295
215   314
216   333
217   356
218   381
219   400
220   422
221   432
222   459
223   475
224   501
225   523
226   543
227   559
228   586
229   603
230   628
231   658
232   670
233   701
234   720
235   740
236   754
237   780
238   803
239   833
240   854
241   872
242   901
243   921
244   943
245   962
246   974
247   986
248  1002
249  1015
250  1034
251  1050
252  1068
253  1080
254  1089
255  1104
256  1110
257  1120
258  1128
259  1139
260  1158
261  1162
262  1172
263  1181
264  1190
265  1197
266  1205
267  1213
268  1219
269  1230
270  1249
271  1255
272  1263
273  1267
274  1274
275  1280
276  1289
277  1296
278  1307
279  1310
280  1310
281  1315
282  1318
283  1322
284  1330
285  1335
286  1341
287  1346
288  1351
289  1357
290  1362
291  1365
292  1369
293  1373
294  1375
295  1381
296  1388
297  1393
298  1396
299  1398
300  1401
301    84
302   105
303   123
304   148
305   169
306   192
307   214
308   242
309   272
310   292
311   308
312   328
313   342
314   369
315   388
316   416
317   445
318   474
319   501
320   527
321   543
322   575
323   599
324   634
325   659
326   687
327   714
328   748
329   774
330   802
331   835
332   850
333   890
334   917
335   941
336   961
337   995
338  1026
339  1061
340  1088
341  1108
342  1139
343  1164
344  1195
345  1224
346  1242
347  1259
348  1282
349  1300
350  1322
351  1339
352  1362
353  1378
354  1389
355  1408
356  1415
357  1426
358  1440
359  1453
360  1474
361  1481
362  1492
363  1508
364  1519
365  1529
366  1538
367  1547
368  1553
369  1565
370  1585
371  1592
372  1600
373  1604
374  1613
375  1620
376  1630
377  1640
378  1652
379  1656
380  1656
381  1662
382  1666
383  1674
384  1683
385  1688
386  1694
387  1700
388  1705
389  1711
390  1717
391  1721
392  1726
393  1731
394  1733
395  1740
396  1748
397  1755
398  1758
399  1762
400  1766
401    99
402   124
403   146
404   175
405   200
406   228
407   253
408   283
409   317
410   341
411   362
412   389
413   408
414   439
415   464
416   496
417   530
418   560
419   590
420   622
421   641
422   679
423   709
424   747
425   775
426   809
427   843
428   881
429   909
430   942
431   982
432  1004
433  1047
434  1076
435  1106
436  1129
437  1165
438  1201
439  1241
440  1272
441  1298
442  1333
443  1366
444  1402
445  1435
446  1455
447  1477
448  1504
449  1526
450  1552
451  1571
452  1597
453  1616
454  1630
455  1651
456  1659
457  1671
458  1687
459  1702
460  1724
461  1734
462  1750
463  1770
464  1782
465  1796
466  1808
467  1817
468  1826
469  1841
470  1861
471  1872
472  1880
473  1885
474  1895
475  1904
476  1915
477  1929
478  1943
479  1949
480  1950
481  1959
482  1965
483  1974
484  1985
485  1993
486  1999
487  2007
488  2012
489  2019
490  2026
491  2031
492  2036
493  2042
494  2044
495  2051
496  2063
497  2072
498  2075
499  2080
500  2084
enrichment.plotter(gene.hic.filt, "adj.P.Val", "min_FDR.H", "Minimum DE FDR of Genes Overlapping Hi-C Contacts", xmax=1, recip=TRUE) #FIGS20A/B
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp     chisq.p Dneither   DE DHiC
1   0.010    0.01 0.05602241 0.06053581 0.800652624     6957  337  450
2   0.010    0.02 0.09243697 0.10059248 0.663978705     6659  324  748
3   0.010    0.03 0.13165266 0.13459557 0.930337299     6409  310  998
4   0.010    0.04 0.15686275 0.15996909 0.928275481     6221  301 1186
5   0.010    0.05 0.17927171 0.18044822 1.000000000     6070  293 1337
6   0.010    0.06 0.20168067 0.20002576 0.990186154     5926  285 1481
7   0.010    0.07 0.21568627 0.21818650 0.958922928     5790  280 1617
8   0.010    0.08 0.24929972 0.23480165 0.550018420     5673  268 1734
9   0.010    0.09 0.26610644 0.25270479 0.593186399     5540  262 1867
10  0.010    0.10 0.27731092 0.26841834 0.743628272     5422  258 1985
11  0.010    0.11 0.28571429 0.28065430 0.874812750     5330  255 2077
12  0.010    0.12 0.29691877 0.29533745 0.993884589     5220  251 2187
13  0.010    0.13 0.30252101 0.30873261 0.840341856     5118  249 2289
14  0.010    0.14 0.31652661 0.32393096 0.803998305     5005  244 2402
15  0.010    0.15 0.33053221 0.33590933 0.870621812     4917  239 2490
16  0.010    0.16 0.33613445 0.34698609 0.700920468     4833  237 2574
17  0.010    0.17 0.35014006 0.35651726 0.840703138     4764  232 2643
18  0.010    0.18 0.36694678 0.36810922 1.000000000     4680  226 2727
19  0.010    0.19 0.39215686 0.37802679 0.611570946     4612  217 2795
20  0.010    0.20 0.40056022 0.39026275 0.724228311     4520  214 2887
21  0.010    0.21 0.41456583 0.40146832 0.644373263     4438  209 2969
22  0.010    0.22 0.43977591 0.41190108 0.298089950     4366  200 3041
23  0.010    0.23 0.44257703 0.42297785 0.476100034     4281  199 3126
24  0.010    0.24 0.44537815 0.43366821 0.687378789     4199  198 3208
25  0.010    0.25 0.44817927 0.44332818 0.893115650     4125  197 3282
26  0.010    0.26 0.45378151 0.45350335 1.000000000     4048  195 3359
27  0.010    0.27 0.45378151 0.46200412 0.791238616     3982  195 3425
28  0.010    0.28 0.46218487 0.47011850 0.800106597     3922  192 3485
29  0.010    0.29 0.47619048 0.48016486 0.920616777     3849  187 3558
30  0.010    0.30 0.49019608 0.49072643 1.000000000     3772  182 3635
31  0.010    0.31 0.49299720 0.49819681 0.883146496     3715  181 3692
32  0.010    0.32 0.50420168 0.50695518 0.958250913     3651  177 3756
33  0.010    0.33 0.51260504 0.51609995 0.935386393     3583  174 3824
34  0.010    0.34 0.51540616 0.52460072 0.762723416     3518  173 3889
35  0.010    0.35 0.52380952 0.53207110 0.790245079     3463  170 3944
36  0.010    0.36 0.52661064 0.54018547 0.636543613     3401  169 4006
37  0.010    0.37 0.53221289 0.54662545 0.613121642     3353  167 4054
38  0.010    0.38 0.54061625 0.55319423 0.663627911     3305  164 4102
39  0.010    0.39 0.54621849 0.56169500 0.583159212     3241  162 4166
40  0.010    0.40 0.55462185 0.56800618 0.639793731     3195  159 4212
41  0.010    0.41 0.55742297 0.57534776 0.517833707     3139  158 4268
42  0.010    0.42 0.57142857 0.58346213 0.676508459     3081  153 4326
43  0.010    0.43 0.57703081 0.59222050 0.587268901     3015  151 4392
44  0.010    0.44 0.58263305 0.59917568 0.550036866     2963  149 4444
45  0.010    0.45 0.58543417 0.60625966 0.441836082     2909  148 4498
46  0.010    0.46 0.58543417 0.61385884 0.282938643     2850  148 4557
47  0.010    0.47 0.59103641 0.61939722 0.282762145     2809  146 4598
48  0.010    0.48 0.59663866 0.62686759 0.248880733     2753  144 4654
49  0.010    0.49 0.60504202 0.63614116 0.232430702     2684  141 4723
50  0.010    0.50 0.61064426 0.64129315 0.238133543     2646  139 4761
51  0.010    0.51 0.62184874 0.64863472 0.303651985     2593  135 4814
52  0.010    0.52 0.63025210 0.65546110 0.332466932     2543  132 4864
53  0.010    0.53 0.63585434 0.66293148 0.293373423     2487  130 4920
54  0.010    0.54 0.63865546 0.67014426 0.215731319     2432  129 4975
55  0.010    0.55 0.64705882 0.67426584 0.286779085     2403  126 5004
56  0.010    0.56 0.65266106 0.67993302 0.283357140     2361  124 5046
57  0.010    0.57 0.65266106 0.68624420 0.179707412     2312  124 5095
58  0.010    0.58 0.65826331 0.69448738 0.143617490     2250  122 5157
59  0.010    0.59 0.66106443 0.70118496 0.101768730     2199  121 5208
60  0.010    0.60 0.66386555 0.70839773 0.066392156     2144  120 5263
61  0.010    0.61 0.66666667 0.71535291 0.042653784     2091  119 5316
62  0.010    0.62 0.68067227 0.72140649 0.089650330     2049  114 5358
63  0.010    0.63 0.69187675 0.72784647 0.132965198     2003  110 5404
64  0.010    0.64 0.69187675 0.73364245 0.077329863     1958  110 5449
65  0.010    0.65 0.69187675 0.73853684 0.046328280     1920  110 5487
66  0.010    0.66 0.70028011 0.74678001 0.044831808     1859  107 5548
67  0.010    0.67 0.70868347 0.75399279 0.048587641     1806  104 5601
68  0.010    0.68 0.72549020 0.76416795 0.089385709     1733   98 5674
69  0.010    0.69 0.73109244 0.77163833 0.071243900     1677   96 5730
70  0.010    0.70 0.73949580 0.77833591 0.081223075     1628   93 5779
71  0.010    0.71 0.73949580 0.78400309 0.042727168     1584   93 5823
72  0.010    0.72 0.74789916 0.78967027 0.055336084     1543   90 5864
73  0.010    0.73 0.75070028 0.79495106 0.040063042     1503   89 5904
74  0.010    0.74 0.76470588 0.80100464 0.090854612     1461   84 5946
75  0.010    0.75 0.76750700 0.80795981 0.055132162     1408   83 5999
76  0.010    0.76 0.77310924 0.81388460 0.050341870     1364   81 6043
77  0.010    0.77 0.78711485 0.82199897 0.090393507     1306   76 6101
78  0.010    0.78 0.78991597 0.82779495 0.061623926     1262   75 6145
79  0.010    0.79 0.80112045 0.83475013 0.093223905     1212   71 6195
80  0.010    0.80 0.80112045 0.84067491 0.043728176     1166   71 6241
81  0.010    0.81 0.82072829 0.85200927 0.103565734     1085   64 6322
82  0.010    0.82 0.82352941 0.85896445 0.058548005     1032   63 6375
83  0.010    0.83 0.83473389 0.86643483 0.084885770      978   59 6429
84  0.010    0.84 0.84593838 0.87467800 0.110186466      918   55 6489
85  0.010    0.85 0.84873950 0.88408037 0.040275437      846   54 6561
86  0.010    0.86 0.85714286 0.89283874 0.031969468      781   51 6626
87  0.010    0.87 0.86554622 0.90352911 0.016532461      701   48 6706
88  0.010    0.88 0.87675070 0.90945389 0.034846297      659   44 6748
89  0.010    0.89 0.88515406 0.91486347 0.049739964      620   41 6787
90  0.010    0.90 0.90196078 0.92168985 0.186928988      573   35 6834
91  0.010    0.91 0.91316527 0.92967543 0.252991424      515   31 6892
92  0.010    0.92 0.91316527 0.93547141 0.099766307      470   31 6937
93  0.010    0.93 0.91596639 0.94397218 0.025227369      405   30 7002
94  0.010    0.94 0.92436975 0.95324575 0.011815614      336   27 7071
95  0.010    0.95 0.93837535 0.96136012 0.030283544      278   22 7129
96  0.010    0.96 0.94677871 0.96780010 0.031549509      231   19 7176
97  0.010    0.97 0.96358543 0.97552808 0.186881383      177   13 7230
98  0.010    0.98 0.97478992 0.98286965 0.319374503      124    9 7283
99  0.010    0.99 0.98879552 0.99356002 0.415923533       46    4 7361
100 0.010    1.00 1.00000000 1.00000000 0.000000000        0    0 7407
101 0.025    0.01 0.05964215 0.06053581 1.000000000     6821  473  440
102 0.025    0.02 0.09542744 0.10059248 0.747760009     6528  455  733
103 0.025    0.03 0.13320080 0.13459557 0.978275449     6283  436  978
104 0.025    0.04 0.16302187 0.15996909 0.896371562     6101  421 1160
105 0.025    0.05 0.18091451 0.18044822 1.000000000     5951  412 1310
106 0.025    0.06 0.20477137 0.20002576 0.827817900     5811  400 1450
107 0.025    0.07 0.21868787 0.21818650 1.000000000     5677  393 1584
108 0.025    0.08 0.24453280 0.23480165 0.632625688     5561  380 1700
109 0.025    0.09 0.26441352 0.25270479 0.567447458     5432  370 1829
110 0.025    0.10 0.27634195 0.26841834 0.716860281     5316  364 1945
111 0.025    0.11 0.28429423 0.28065430 0.891372811     5225  360 2036
112 0.025    0.12 0.29423459 0.29533745 0.995585801     5116  355 2145
113 0.025    0.13 0.30616302 0.30873261 0.936957260     5018  349 2243
114 0.025    0.14 0.32007952 0.32393096 0.887392027     4907  342 2354
115 0.025    0.15 0.33200795 0.33590933 0.886481636     4820  336 2441
116 0.025    0.16 0.33598410 0.34698609 0.625838696     4736  334 2525
117 0.025    0.17 0.34990060 0.35651726 0.785434046     4669  327 2592
118 0.025    0.18 0.36580517 0.36810922 0.949771627     4587  319 2674
119 0.025    0.19 0.38767396 0.37802679 0.678975808     4521  308 2740
120 0.025    0.20 0.39761431 0.39026275 0.762461205     4431  303 2830
121 0.025    0.21 0.40755467 0.40146832 0.809616160     4349  298 2912
122 0.025    0.22 0.42942346 0.41190108 0.436086744     4279  287 2982
123 0.025    0.23 0.43339960 0.42297785 0.658078120     4195  285 3066
124 0.025    0.24 0.43737575 0.43366821 0.898954290     4114  283 3147
125 0.025    0.25 0.43936382 0.44332818 0.889713900     4040  282 3221
126 0.025    0.26 0.44930417 0.45350335 0.881308379     3966  277 3295
127 0.025    0.27 0.45129225 0.46200412 0.651233430     3901  276 3360
128 0.025    0.28 0.46123260 0.47011850 0.713840475     3843  271 3418
129 0.025    0.29 0.47514911 0.48016486 0.851906542     3772  264 3489
130 0.025    0.30 0.48707753 0.49072643 0.901979268     3696  258 3565
131 0.025    0.31 0.49105368 0.49819681 0.775479434     3640  256 3621
132 0.025    0.32 0.50298211 0.50695518 0.890090387     3578  250 3683
133 0.025    0.33 0.51292247 0.51609995 0.919290631     3512  245 3749
134 0.025    0.34 0.52087475 0.52460072 0.899044193     3450  241 3811
135 0.025    0.35 0.52683897 0.53207110 0.843842351     3395  238 3866
136 0.025    0.36 0.53479125 0.54018547 0.837762818     3336  234 3925
137 0.025    0.37 0.54075547 0.54662545 0.820306555     3289  231 3972
138 0.025    0.38 0.54870775 0.55319423 0.870585870     3242  227 4019
139 0.025    0.39 0.55467197 0.56169500 0.778099737     3179  224 4082
140 0.025    0.40 0.56262425 0.56800618 0.837234219     3134  220 4127
141 0.025    0.41 0.57057654 0.57534776 0.859334999     3081  216 4180
142 0.025    0.42 0.58250497 0.58346213 1.000000000     3024  210 4237
143 0.025    0.43 0.59045726 0.59222050 0.971042222     2960  206 4301
144 0.025    0.44 0.59443340 0.59917568 0.859210558     2908  204 4353
145 0.025    0.45 0.59840954 0.60625966 0.744848493     2855  202 4406
146 0.025    0.46 0.60437376 0.61385884 0.685869924     2799  199 4462
147 0.025    0.47 0.60834990 0.61939722 0.631090200     2758  197 4503
148 0.025    0.48 0.61232604 0.62686759 0.515928645     2702  195 4559
149 0.025    0.49 0.62027833 0.63614116 0.473534988     2634  191 4627
150 0.025    0.50 0.62425447 0.64129315 0.437855930     2596  189 4665
151 0.025    0.51 0.63419483 0.64863472 0.513635736     2544  184 4717
152 0.025    0.52 0.64015905 0.65546110 0.485016268     2494  181 4767
153 0.025    0.53 0.64612326 0.66293148 0.437833235     2439  178 4822
154 0.025    0.54 0.65208748 0.67014426 0.399984192     2386  175 4875
155 0.025    0.55 0.66003976 0.67426584 0.512596910     2358  171 4903
156 0.025    0.56 0.66600398 0.67993302 0.520194405     2317  168 4944
157 0.025    0.57 0.66799205 0.68624420 0.388382165     2269  167 4992
158 0.025    0.58 0.67594433 0.69448738 0.376935645     2209  163 5052
159 0.025    0.59 0.67793241 0.70118496 0.259431700     2158  162 5103
160 0.025    0.60 0.68190855 0.70839773 0.193284336     2104  160 5157
161 0.025    0.61 0.68787276 0.71535291 0.173439349     2053  157 5208
162 0.025    0.62 0.69781312 0.72140649 0.242366590     2011  152 5250
163 0.025    0.63 0.70775348 0.72784647 0.319637974     1966  147 5295
164 0.025    0.64 0.70775348 0.73364245 0.191530398     1921  147 5340
165 0.025    0.65 0.70974155 0.73853684 0.142310440     1884  146 5377
166 0.025    0.66 0.71570577 0.74678001 0.108665465     1823  143 5438
167 0.025    0.67 0.72365805 0.75399279 0.114119863     1771  139 5490
168 0.025    0.68 0.73956262 0.76416795 0.197089016     1700  131 5561
169 0.025    0.69 0.74353877 0.77163833 0.134262246     1644  129 5617
170 0.025    0.70 0.74950298 0.77833591 0.120100567     1595  126 5666
171 0.025    0.71 0.75149105 0.78400309 0.075691406     1552  125 5709
172 0.025    0.72 0.76143141 0.78967027 0.121049316     1513  120 5748
173 0.025    0.73 0.76341948 0.79495106 0.079406983     1473  119 5788
174 0.025    0.74 0.77335984 0.80100464 0.121598109     1431  114 5830
175 0.025    0.75 0.77534791 0.80795981 0.062669298     1378  113 5883
176 0.025    0.76 0.78131213 0.81388460 0.059879028     1335  110 5926
177 0.025    0.77 0.79125249 0.82199897 0.071252261     1277  105 5984
178 0.025    0.78 0.79324056 0.82779495 0.039261035     1233  104 6028
179 0.025    0.79 0.80516899 0.83475013 0.074253510     1185   98 6076
180 0.025    0.80 0.80914513 0.84067491 0.052990319     1141   96 6120
181 0.025    0.81 0.82703777 0.85200927 0.117348091     1062   87 6199
182 0.025    0.82 0.83101392 0.85896445 0.072472288     1010   85 6251
183 0.025    0.83 0.83896620 0.86643483 0.071096803      956   81 6305
184 0.025    0.84 0.84691849 0.87467800 0.060813822      896   77 6365
185 0.025    0.85 0.84890656 0.88408037 0.013281537      824   76 6437
186 0.025    0.86 0.85487078 0.89283874 0.005568515      759   73 6502
187 0.025    0.87 0.86481113 0.90352911 0.003043548      681   68 6580
188 0.025    0.88 0.87475149 0.90945389 0.006445505      640   63 6621
189 0.025    0.89 0.88469185 0.91486347 0.015324859      603   58 6658
190 0.025    0.90 0.89860835 0.92168985 0.056564786      557   51 6704
191 0.025    0.91 0.91451292 0.92967543 0.198762266      503   43 6758
192 0.025    0.92 0.92047714 0.93547141 0.186329337      461   40 6800
193 0.025    0.93 0.92445328 0.94397218 0.061746956      397   38 6864
194 0.025    0.94 0.93041750 0.95324575 0.016459029      328   35 6933
195 0.025    0.95 0.94433400 0.96136012 0.053716755      272   28 6989
196 0.025    0.96 0.95427435 0.96780010 0.099694256      227   23 7034
197 0.025    0.97 0.96819085 0.97552808 0.341046705      174   16 7087
198 0.025    0.98 0.97813121 0.98286965 0.503343775      122   11 7139
199 0.025    0.99 0.99005964 0.99356002 0.467435863       45    5 7216
200 0.025    1.00 1.00000000 1.00000000 0.000000000        0    0 7261
201 0.050    0.01 0.06424581 0.06053581 0.722834149     6624  670  424
202 0.050    0.02 0.10195531 0.10059248 0.950527352     6340  643  708
203 0.050    0.03 0.13547486 0.13459557 0.988118676     6100  619  948
204 0.050    0.04 0.16620112 0.15996909 0.671600828     5925  597 1123
205 0.050    0.05 0.18156425 0.18044822 0.975664616     5777  586 1271
206 0.050    0.06 0.20391061 0.20002576 0.822975727     5641  570 1407
207 0.050    0.07 0.22346369 0.21818650 0.755529424     5514  556 1534
208 0.050    0.08 0.24720670 0.23480165 0.437957152     5402  539 1646
209 0.050    0.09 0.26256983 0.25270479 0.553571566     5274  528 1774
210 0.050    0.10 0.27932961 0.26841834 0.517462717     5164  516 1884
211 0.050    0.11 0.29050279 0.28065430 0.567371353     5077  508 1971
212 0.050    0.12 0.30586592 0.29533745 0.545067059     4974  497 2074
213 0.050    0.13 0.31703911 0.30873261 0.643707139     4878  489 2170
214 0.050    0.14 0.32681564 0.32393096 0.895609587     4767  482 2281
215 0.050    0.15 0.33659218 0.33590933 1.000000000     4681  475 2367
216 0.050    0.16 0.34357542 0.34698609 0.872859514     4600  470 2448
217 0.050    0.17 0.36033520 0.35651726 0.854861769     4538  458 2510
218 0.050    0.18 0.37430168 0.36810922 0.749020878     4458  448 2590
219 0.050    0.19 0.39106145 0.37802679 0.474914770     4393  436 2655
220 0.050    0.20 0.39944134 0.39026275 0.625385818     4304  430 2744
221 0.050    0.21 0.40782123 0.40146832 0.745964463     4223  424 2825
222 0.050    0.22 0.42458101 0.41190108 0.494170694     4154  412 2894
223 0.050    0.23 0.42737430 0.42297785 0.833488584     4070  410 2978
224 0.050    0.24 0.43854749 0.43366821 0.812708152     3995  402 3053
225 0.050    0.25 0.44413408 0.44332818 0.995147740     3924  398 3124
226 0.050    0.26 0.45670391 0.45350335 0.887743736     3854  389 3194
227 0.050    0.27 0.45810056 0.46200412 0.856715309     3789  388 3259
228 0.050    0.28 0.46648045 0.47011850 0.868615836     3732  382 3316
229 0.050    0.29 0.47625698 0.48016486 0.856823301     3661  375 3387
230 0.050    0.30 0.48603352 0.49072643 0.822438043     3586  368 3462
231 0.050    0.31 0.49162011 0.49819681 0.741260912     3532  364 3516
232 0.050    0.32 0.50418994 0.50695518 0.907567440     3473  355 3575
233 0.050    0.33 0.52094972 0.51609995 0.815525762     3414  343 3634
234 0.050    0.34 0.52793296 0.52460072 0.882245165     3353  338 3695
235 0.050    0.35 0.53491620 0.53207110 0.903824747     3300  333 3748
236 0.050    0.36 0.54469274 0.54018547 0.830049072     3244  326 3804
237 0.050    0.37 0.55027933 0.54662545 0.867577032     3198  322 3850
238 0.050    0.38 0.55726257 0.55319423 0.849018663     3152  317 3896
239 0.050    0.39 0.56564246 0.56169500 0.854087455     3092  311 3956
240 0.050    0.40 0.57402235 0.56800618 0.763033792     3049  305 3999
241 0.050    0.41 0.58240223 0.57534776 0.717992887     2998  299 4050
242 0.050    0.42 0.59497207 0.58346213 0.537948432     2944  290 4104
243 0.050    0.43 0.60474860 0.59222050 0.498999451     2883  283 4165
244 0.050    0.44 0.61033520 0.59917568 0.548835772     2833  279 4215
245 0.050    0.45 0.61452514 0.60625966 0.663580278     2781  276 4267
246 0.050    0.46 0.61871508 0.61385884 0.810448317     2725  273 4323
247 0.050    0.47 0.62290503 0.61939722 0.870906463     2685  270 4363
248 0.050    0.48 0.63128492 0.62686759 0.829019091     2633  264 4415
249 0.050    0.49 0.63687151 0.63614116 0.998508634     2565  260 4483
250 0.050    0.50 0.64525140 0.64129315 0.848614327     2531  254 4517
251 0.050    0.51 0.65223464 0.64863472 0.864463030     2479  249 4569
252 0.050    0.52 0.65782123 0.65546110 0.921766003     2430  245 4618
253 0.050    0.53 0.66340782 0.66293148 1.000000000     2376  241 4672
254 0.050    0.54 0.66899441 0.67014426 0.978482950     2324  237 4724
255 0.050    0.55 0.67597765 0.67426584 0.951570441     2297  232 4751
256 0.050    0.56 0.68575419 0.67993302 0.757772907     2260  225 4788
257 0.050    0.57 0.69134078 0.68624420 0.790083594     2215  221 4833
258 0.050    0.58 0.70111732 0.69448738 0.717610991     2158  214 4890
259 0.050    0.59 0.70530726 0.70118496 0.833606892     2109  211 4939
260 0.050    0.60 0.70810056 0.70839773 1.000000000     2055  209 4993
261 0.050    0.61 0.71648045 0.71535291 0.978688546     2007  203 5041
262 0.050    0.62 0.72765363 0.72140649 0.728133786     1968  195 5080
263 0.050    0.63 0.73743017 0.72784647 0.575015673     1925  188 5123
264 0.050    0.64 0.74022346 0.73364245 0.708599184     1882  186 5166
265 0.050    0.65 0.74301676 0.73853684 0.809023919     1846  184 5202
266 0.050    0.66 0.74720670 0.74678001 1.000000000     1785  181 5263
267 0.050    0.67 0.75418994 0.75399279 1.000000000     1734  176 5314
268 0.050    0.68 0.76815642 0.76416795 0.827691283     1665  166 5383
269 0.050    0.69 0.77234637 0.77163833 0.999481459     1610  163 5438
270 0.050    0.70 0.77793296 0.77833591 1.000000000     1562  159 5486
271 0.050    0.71 0.78072626 0.78400309 0.860313090     1520  157 5528
272 0.050    0.72 0.78770950 0.78967027 0.930673317     1481  152 5567
273 0.050    0.73 0.78910615 0.79495106 0.720341065     1441  151 5607
274 0.050    0.74 0.79888268 0.80100464 0.920230023     1401  144 5647
275 0.050    0.75 0.80307263 0.80795981 0.765202276     1350  141 5698
276 0.050    0.76 0.80865922 0.81388460 0.743917412     1308  137 5740
277 0.050    0.77 0.81843575 0.82199897 0.833400154     1252  130 5796
278 0.050    0.78 0.82262570 0.82779495 0.739460815     1210  127 5838
279 0.050    0.79 0.83100559 0.83475013 0.817823806     1162  121 5886
280 0.050    0.80 0.83659218 0.84067491 0.795085580     1120  117 5928
281 0.050    0.81 0.85474860 0.85200927 0.871758575     1045  104 6003
282 0.050    0.82 0.85893855 0.85896445 1.000000000      994  101 6054
283 0.050    0.83 0.86731844 0.86643483 0.987795681      942   95 6106
284 0.050    0.84 0.87430168 0.87467800 1.000000000      883   90 6165
285 0.050    0.85 0.87709497 0.88408037 0.581251737      812   88 6236
286 0.050    0.86 0.88128492 0.89283874 0.324318121      747   85 6301
287 0.050    0.87 0.88966480 0.90352911 0.210416536      670   79 6378
288 0.050    0.88 0.89664804 0.90945389 0.236041217      629   74 6419
289 0.050    0.89 0.90363128 0.91486347 0.289131233      592   69 6456
290 0.050    0.90 0.91480447 0.92168985 0.517781613      547   61 6501
291 0.050    0.91 0.92597765 0.92967543 0.741816252      493   53 6555
292 0.050    0.92 0.93435754 0.93547141 0.962115185      454   47 6594
293 0.050    0.93 0.93854749 0.94397218 0.563816756      391   44 6657
294 0.050    0.94 0.94413408 0.95324575 0.263038933      323   40 6725
295 0.050    0.95 0.95530726 0.96136012 0.435250544      268   32 6780
296 0.050    0.96 0.96508380 0.96780010 0.748177841      225   25 6823
297 0.050    0.97 0.97625698 0.97552808 0.995564929      173   17 6875
298 0.050    0.98 0.98324022 0.98286965 1.000000000      121   12 6927
299 0.050    0.99 0.99162011 0.99356002 0.662897217       44    6 7004
300 0.050    1.00 1.00000000 1.00000000 0.000000000        0    0 7048
301 0.075    0.01 0.07188841 0.06053581 0.139929431     6429  865  403
302 0.075    0.02 0.11802575 0.10059248 0.067521852     6161  822  671
303 0.075    0.03 0.14914163 0.13459557 0.181578898     5926  793  906
304 0.075    0.04 0.17489270 0.15996909 0.201504106     5753  769 1079
305 0.075    0.05 0.19098712 0.18044822 0.397284237     5609  754 1223
306 0.075    0.06 0.21137339 0.20002576 0.379095251     5476  735 1356
307 0.075    0.07 0.23175966 0.21818650 0.304300611     5354  716 1478
308 0.075    0.08 0.25429185 0.23480165 0.145603799     5246  695 1586
309 0.075    0.09 0.27145923 0.25270479 0.172459617     5123  679 1709
310 0.075    0.10 0.28648069 0.26841834 0.198052761     5015  665 1817
311 0.075    0.11 0.29828326 0.28065430 0.215709160     4931  654 1901
312 0.075    0.12 0.31652361 0.29533745 0.140716932     4834  637 1998
313 0.075    0.13 0.32939914 0.30873261 0.156161118     4742  625 2090
314 0.075    0.14 0.33798283 0.32393096 0.347266725     4632  617 2200
315 0.075    0.15 0.34656652 0.33590933 0.485571145     4547  609 2285
316 0.075    0.16 0.35193133 0.34698609 0.763092156     4466  604 2366
317 0.075    0.17 0.36587983 0.35651726 0.548704082     4405  591 2427
318 0.075    0.18 0.37768240 0.36810922 0.542003686     4326  580 2506
319 0.075    0.19 0.39163090 0.37802679 0.380457125     4262  567 2570
320 0.075    0.20 0.39914163 0.39026275 0.577822969     4174  560 2658
321 0.075    0.21 0.40772532 0.40146832 0.704101299     4095  552 2737
322 0.075    0.22 0.42274678 0.41190108 0.495440992     4028  538 2804
323 0.075    0.23 0.42703863 0.42297785 0.816410779     3946  534 2886
324 0.075    0.24 0.43884120 0.43366821 0.760764983     3874  523 2958
325 0.075    0.25 0.44527897 0.44332818 0.926179408     3805  517 3027
326 0.075    0.26 0.45600858 0.45350335 0.897593689     3736  507 3096
327 0.075    0.27 0.46459227 0.46200412 0.893459259     3678  499 3154
328 0.075    0.28 0.47424893 0.47011850 0.814717083     3624  490 3208
329 0.075    0.29 0.48497854 0.48016486 0.780538573     3556  480 3276
330 0.075    0.30 0.49356223 0.49072643 0.881012355     3482  472 3350
331 0.075    0.31 0.50000000 0.49819681 0.934289275     3430  466 3402
332 0.075    0.32 0.50965665 0.50695518 0.887924719     3371  457 3461
333 0.075    0.33 0.52360515 0.51609995 0.649957261     3313  444 3519
334 0.075    0.34 0.53218884 0.52460072 0.645846544     3255  436 3577
335 0.075    0.35 0.53862661 0.53207110 0.694629408     3203  430 3629
336 0.075    0.36 0.54613734 0.54018547 0.723619612     3147  423 3685
337 0.075    0.37 0.55150215 0.54662545 0.776612682     3102  418 3730
338 0.075    0.38 0.56008584 0.55319423 0.677403380     3059  410 3773
339 0.075    0.39 0.56866953 0.56169500 0.672826495     3001  402 3831
340 0.075    0.40 0.57725322 0.56800618 0.567133374     2960  394 3872
341 0.075    0.41 0.58369099 0.57534776 0.607250431     2909  388 3923
342 0.075    0.42 0.59442060 0.58346213 0.491447486     2856  378 3976
343 0.075    0.43 0.60300429 0.59222050 0.497373280     2796  370 4036
344 0.075    0.44 0.61051502 0.59917568 0.473127349     2749  363 4083
345 0.075    0.45 0.61587983 0.60625966 0.545133346     2699  358 4133
346 0.075    0.46 0.62017167 0.61385884 0.699406976     2644  354 4188
347 0.075    0.47 0.62339056 0.61939722 0.816766117     2604  351 4228
348 0.075    0.48 0.63304721 0.62686759 0.704143919     2555  342 4277
349 0.075    0.49 0.63733906 0.63614116 0.964313823     2487  338 4345
350 0.075    0.50 0.64377682 0.64129315 0.894884650     2453  332 4379
351 0.075    0.51 0.65236052 0.64863472 0.827883187     2404  324 4428
352 0.075    0.52 0.65879828 0.65546110 0.847898112     2357  318 4475
353 0.075    0.53 0.66416309 0.66293148 0.961829819     2304  313 4528
354 0.075    0.54 0.67274678 0.67014426 0.886281253     2256  305 4576
355 0.075    0.55 0.67918455 0.67426584 0.760887383     2230  299 4602
356 0.075    0.56 0.68669528 0.67993302 0.664051132     2193  292 4639
357 0.075    0.57 0.69206009 0.68624420 0.711176432     2149  287 4683
358 0.075    0.58 0.70064378 0.69448738 0.691320578     2093  279 4739
359 0.075    0.59 0.70600858 0.70118496 0.760511715     2046  274 4786
360 0.075    0.60 0.71030043 0.70839773 0.922069096     1994  270 4838
361 0.075    0.61 0.71888412 0.71535291 0.829000555     1948  262 4884
362 0.075    0.62 0.73068670 0.72140649 0.525596286     1912  251 4920
363 0.075    0.63 0.73819742 0.72784647 0.472968814     1869  244 4963
364 0.075    0.64 0.74141631 0.73364245 0.594155915     1827  241 5005
365 0.075    0.65 0.74463519 0.73853684 0.680402330     1792  238 5040
366 0.075    0.66 0.75000000 0.74678001 0.840829362     1733  233 5099
367 0.075    0.67 0.75536481 0.75399279 0.949657176     1682  228 5150
368 0.075    0.68 0.76716738 0.76416795 0.850237993     1614  217 5218
369 0.075    0.69 0.77038627 0.77163833 0.955757850     1559  214 5273
370 0.075    0.70 0.77575107 0.77833591 0.872494232     1512  209 5320
371 0.075    0.71 0.77789700 0.78400309 0.659594562     1470  207 5362
372 0.075    0.72 0.78540773 0.78967027 0.766049634     1433  200 5399
373 0.075    0.73 0.78969957 0.79495106 0.703895818     1396  196 5436
374 0.075    0.74 0.79721030 0.80100464 0.790574809     1356  189 5476
375 0.075    0.75 0.80042918 0.80795981 0.563360335     1305  186 5527
376 0.075    0.76 0.80579399 0.81388460 0.527604395     1264  181 5568
377 0.075    0.77 0.81652361 0.82199897 0.674337480     1211  171 5621
378 0.075    0.78 0.82403433 0.82779495 0.781080667     1173  164 5659
379 0.075    0.79 0.83047210 0.83475013 0.743022925     1125  158 5707
380 0.075    0.80 0.83476395 0.84067491 0.632705611     1083  154 5749
381 0.075    0.81 0.84978541 0.85200927 0.877096778     1009  140 5823
382 0.075    0.82 0.85407725 0.85896445 0.684151563      959  136 5873
383 0.075    0.83 0.86266094 0.86643483 0.756779492      909  128 5923
384 0.075    0.84 0.87017167 0.87467800 0.696371731      852  121 5980
385 0.075    0.85 0.87446352 0.88408037 0.355947049      783  117 6049
386 0.075    0.86 0.87875536 0.89283874 0.154065821      719  113 6113
387 0.075    0.87 0.88841202 0.90352911 0.107999655      645  104 6187
388 0.075    0.88 0.89592275 0.90945389 0.140555562      606   97 6226
389 0.075    0.89 0.90236052 0.91486347 0.162887251      570   91 6262
390 0.075    0.90 0.91309013 0.92168985 0.328691164      527   81 6305
391 0.075    0.91 0.92381974 0.92967543 0.498390762      475   71 6357
392 0.075    0.92 0.93025751 0.93547141 0.535540018      436   65 6396
393 0.075    0.93 0.93669528 0.94397218 0.340157153      376   59 6456
394 0.075    0.94 0.94098712 0.95324575 0.070754028      308   55 6524
395 0.075    0.95 0.95171674 0.96136012 0.124108944      255   45 6577
396 0.075    0.96 0.96137339 0.96780010 0.277524044      214   36 6618
397 0.075    0.97 0.97317597 0.97552808 0.702143270      165   25 6667
398 0.075    0.98 0.98175966 0.98286965 0.885623480      116   17 6716
399 0.075    0.99 0.99034335 0.99356002 0.275517517       41    9 6791
400 0.075    1.00 1.00000000 1.00000000 0.000000000        0    0 6832
401 0.100    0.01 0.07416880 0.06053581 0.039535617     6208 1086  383
402 0.100    0.02 0.12105712 0.10059248 0.013272120     5952 1031  639
403 0.100    0.03 0.15260017 0.13459557 0.055548558     5725  994  866
404 0.100    0.04 0.17817562 0.15996909 0.071392693     5558  964 1033
405 0.100    0.05 0.19522592 0.18044822 0.165373091     5419  944 1172
406 0.100    0.06 0.21909633 0.20002576 0.083178631     5295  916 1296
407 0.100    0.07 0.23870418 0.21818650 0.070565846     5177  893 1414
408 0.100    0.08 0.26086957 0.23480165 0.024533853     5074  867 1517
409 0.100    0.09 0.27706735 0.25270479 0.040610689     4954  848 1637
410 0.100    0.10 0.29070759 0.26841834 0.066661004     4848  832 1743
411 0.100    0.11 0.30434783 0.28065430 0.054242628     4769  816 1822
412 0.100    0.12 0.31884058 0.29533745 0.060057790     4672  799 1919
413 0.100    0.13 0.33162830 0.30873261 0.070609396     4583  784 2008
414 0.100    0.14 0.34271100 0.32393096 0.144875453     4478  771 2113
415 0.100    0.15 0.35038363 0.33590933 0.268889349     4394  762 2197
416 0.100    0.16 0.35720375 0.34698609 0.444499765     4316  754 2275
417 0.100    0.17 0.37169650 0.35651726 0.252228939     4259  737 2332
418 0.100    0.18 0.38277920 0.36810922 0.272284180     4182  724 2409
419 0.100    0.19 0.39386189 0.37802679 0.237506400     4118  711 2473
420 0.100    0.20 0.39982950 0.39026275 0.486101219     4030  704 2561
421 0.100    0.21 0.41261722 0.40146832 0.416155367     3958  689 2633
422 0.100    0.22 0.42796249 0.41190108 0.237660400     3895  671 2696
423 0.100    0.23 0.43307758 0.42297785 0.466703686     3815  665 2776
424 0.100    0.24 0.44757033 0.43366821 0.312119745     3749  648 2842
425 0.100    0.25 0.45609548 0.44332818 0.355781273     3684  638 2907
426 0.100    0.26 0.46632566 0.45350335 0.354662490     3617  626 2974
427 0.100    0.27 0.47485081 0.46200412 0.354413415     3561  616 3030
428 0.100    0.28 0.48422847 0.47011850 0.308143831     3509  605 3082
429 0.100    0.29 0.49360614 0.48016486 0.332869047     3442  594 3149
430 0.100    0.30 0.50298380 0.49072643 0.379008780     3371  583 3220
431 0.100    0.31 0.51150895 0.49819681 0.338065225     3323  573 3268
432 0.100    0.32 0.52088662 0.50695518 0.315317544     3266  562 3325
433 0.100    0.33 0.53452685 0.51609995 0.180591811     3211  546 3380
434 0.100    0.34 0.54305200 0.52460072 0.179700441     3155  536 3436
435 0.100    0.35 0.54816709 0.53207110 0.243066891     3103  530 3488
436 0.100    0.36 0.55498721 0.54018547 0.283630239     3048  522 3543
437 0.100    0.37 0.56010230 0.54662545 0.329818316     3004  516 3587
438 0.100    0.38 0.56947997 0.55319423 0.235706288     2964  505 3627
439 0.100    0.39 0.57630009 0.56169500 0.288132051     2906  497 3685
440 0.100    0.40 0.58397272 0.56800618 0.243548127     2866  488 3725
441 0.100    0.41 0.59079284 0.57534776 0.258704688     2817  480 3774
442 0.100    0.42 0.59931799 0.58346213 0.244658478     2764  470 3827
443 0.100    0.43 0.60784314 0.59222050 0.250357802     2706  460 3885
444 0.100    0.44 0.61466326 0.59917568 0.253280432     2660  452 3931
445 0.100    0.45 0.61892583 0.60625966 0.351731030     2610  447 3981
446 0.100    0.46 0.62318841 0.61385884 0.496651652     2556  442 4035
447 0.100    0.47 0.62574595 0.61939722 0.650247777     2516  439 4075
448 0.100    0.48 0.63597613 0.62686759 0.504571413     2470  427 4121
449 0.100    0.49 0.64109122 0.63614116 0.726696539     2404  421 4187
450 0.100    0.50 0.64705882 0.64129315 0.679005629     2371  414 4220
451 0.100    0.51 0.65643649 0.64863472 0.565774123     2325  403 4266
452 0.100    0.52 0.66410912 0.65546110 0.520149694     2281  394 4310
453 0.100    0.53 0.67263427 0.66293148 0.465713137     2233  384 4358
454 0.100    0.54 0.67945439 0.67014426 0.482441851     2185  376 4406
455 0.100    0.55 0.68456948 0.67426584 0.433363575     2159  370 4432
456 0.100    0.56 0.69224211 0.67993302 0.343713656     2124  361 4467
457 0.100    0.57 0.69735720 0.68624420 0.391940584     2081  355 4510
458 0.100    0.58 0.70502984 0.69448738 0.414288709     2026  346 4565
459 0.100    0.59 0.71099744 0.70118496 0.445918882     1981  339 4610
460 0.100    0.60 0.71526002 0.70839773 0.598623766     1930  334 4661
461 0.100    0.61 0.72293265 0.71535291 0.555674903     1885  325 4706
462 0.100    0.62 0.73401535 0.72140649 0.312429470     1851  312 4740
463 0.100    0.63 0.74254049 0.72784647 0.233402276     1811  302 4780
464 0.100    0.64 0.74680307 0.73364245 0.284248148     1771  297 4820
465 0.100    0.65 0.75021313 0.73853684 0.341272978     1737  293 4854
466 0.100    0.66 0.75532822 0.74678001 0.487510179     1679  287 4912
467 0.100    0.67 0.76214834 0.75399279 0.504700978     1631  279 4960
468 0.100    0.68 0.77408355 0.76416795 0.406022251     1566  265 5025
469 0.100    0.69 0.77749361 0.77163833 0.630694509     1512  261 5079
470 0.100    0.70 0.78346121 0.77833591 0.674100145     1467  254 5124
471 0.100    0.71 0.78772379 0.78400309 0.766018060     1428  249 5163
472 0.100    0.72 0.79369139 0.78967027 0.742996782     1391  242 5200
473 0.100    0.73 0.79795396 0.79495106 0.812477064     1355  237 5236
474 0.100    0.74 0.80562660 0.80100464 0.696059848     1317  228 5274
475 0.100    0.75 0.80818414 0.80795981 1.000000000     1266  225 5325
476 0.100    0.76 0.81500426 0.81388460 0.947197311     1228  217 5363
477 0.100    0.77 0.82438193 0.82199897 0.849192603     1176  206 5415
478 0.100    0.78 0.83120205 0.82779495 0.769159633     1139  198 5452
479 0.100    0.79 0.83631714 0.83475013 0.909101885     1091  192 5500
480 0.100    0.80 0.83972720 0.84067491 0.957760801     1049  188 5542
481 0.100    0.81 0.85421995 0.85200927 0.851818667      978  171 5613
482 0.100    0.82 0.85763001 0.85896445 0.922732253      928  167 5663
483 0.100    0.83 0.86445013 0.86643483 0.864781130      878  159 5713
484 0.100    0.84 0.87212276 0.87467800 0.811083253      823  150 5768
485 0.100    0.85 0.87809037 0.88408037 0.518253735      757  143 5834
486 0.100    0.86 0.88235294 0.89283874 0.226702732      694  138 5897
487 0.100    0.87 0.89343564 0.90352911 0.223542653      624  125 5967
488 0.100    0.88 0.90110827 0.90945389 0.304965352      587  116 6004
489 0.100    0.89 0.90707587 0.91486347 0.326851232      552  109 6039
490 0.100    0.90 0.91645354 0.92168985 0.505714396      510   98 6081
491 0.100    0.91 0.92497869 0.92967543 0.534710614      458   88 6133
492 0.100    0.92 0.93009378 0.93547141 0.453785969      419   82 6172
493 0.100    0.93 0.93520887 0.94397218 0.177800701      359   76 6232
494 0.100    0.94 0.94373402 0.95324575 0.109655092      297   66 6294
495 0.100    0.95 0.95481671 0.96136012 0.238083633      247   53 6344
496 0.100    0.96 0.96419437 0.96780010 0.503176101      208   42 6383
497 0.100    0.97 0.97442455 0.97552808 0.870567064      160   30 6431
498 0.100    0.98 0.98294970 0.98286965 1.000000000      113   20 6478
499 0.100    0.99 0.99232737 0.99356002 0.707856473       41    9 6550
500 0.100    1.00 1.00000000 1.00000000 0.000000000        0    0 6591
    Dboth
1      20
2      33
3      47
4      56
5      64
6      72
7      77
8      89
9      95
10     99
11    102
12    106
13    108
14    113
15    118
16    120
17    125
18    131
19    140
20    143
21    148
22    157
23    158
24    159
25    160
26    162
27    162
28    165
29    170
30    175
31    176
32    180
33    183
34    184
35    187
36    188
37    190
38    193
39    195
40    198
41    199
42    204
43    206
44    208
45    209
46    209
47    211
48    213
49    216
50    218
51    222
52    225
53    227
54    228
55    231
56    233
57    233
58    235
59    236
60    237
61    238
62    243
63    247
64    247
65    247
66    250
67    253
68    259
69    261
70    264
71    264
72    267
73    268
74    273
75    274
76    276
77    281
78    282
79    286
80    286
81    293
82    294
83    298
84    302
85    303
86    306
87    309
88    313
89    316
90    322
91    326
92    326
93    327
94    330
95    335
96    338
97    344
98    348
99    353
100   357
101    30
102    48
103    67
104    82
105    91
106   103
107   110
108   123
109   133
110   139
111   143
112   148
113   154
114   161
115   167
116   169
117   176
118   184
119   195
120   200
121   205
122   216
123   218
124   220
125   221
126   226
127   227
128   232
129   239
130   245
131   247
132   253
133   258
134   262
135   265
136   269
137   272
138   276
139   279
140   283
141   287
142   293
143   297
144   299
145   301
146   304
147   306
148   308
149   312
150   314
151   319
152   322
153   325
154   328
155   332
156   335
157   336
158   340
159   341
160   343
161   346
162   351
163   356
164   356
165   357
166   360
167   364
168   372
169   374
170   377
171   378
172   383
173   384
174   389
175   390
176   393
177   398
178   399
179   405
180   407
181   416
182   418
183   422
184   426
185   427
186   430
187   435
188   440
189   445
190   452
191   460
192   463
193   465
194   468
195   475
196   480
197   487
198   492
199   498
200   503
201    46
202    73
203    97
204   119
205   130
206   146
207   160
208   177
209   188
210   200
211   208
212   219
213   227
214   234
215   241
216   246
217   258
218   268
219   280
220   286
221   292
222   304
223   306
224   314
225   318
226   327
227   328
228   334
229   341
230   348
231   352
232   361
233   373
234   378
235   383
236   390
237   394
238   399
239   405
240   411
241   417
242   426
243   433
244   437
245   440
246   443
247   446
248   452
249   456
250   462
251   467
252   471
253   475
254   479
255   484
256   491
257   495
258   502
259   505
260   507
261   513
262   521
263   528
264   530
265   532
266   535
267   540
268   550
269   553
270   557
271   559
272   564
273   565
274   572
275   575
276   579
277   586
278   589
279   595
280   599
281   612
282   615
283   621
284   626
285   628
286   631
287   637
288   642
289   647
290   655
291   663
292   669
293   672
294   676
295   684
296   691
297   699
298   704
299   710
300   716
301    67
302   110
303   139
304   163
305   178
306   197
307   216
308   237
309   253
310   267
311   278
312   295
313   307
314   315
315   323
316   328
317   341
318   352
319   365
320   372
321   380
322   394
323   398
324   409
325   415
326   425
327   433
328   442
329   452
330   460
331   466
332   475
333   488
334   496
335   502
336   509
337   514
338   522
339   530
340   538
341   544
342   554
343   562
344   569
345   574
346   578
347   581
348   590
349   594
350   600
351   608
352   614
353   619
354   627
355   633
356   640
357   645
358   653
359   658
360   662
361   670
362   681
363   688
364   691
365   694
366   699
367   704
368   715
369   718
370   723
371   725
372   732
373   736
374   743
375   746
376   751
377   761
378   768
379   774
380   778
381   792
382   796
383   804
384   811
385   815
386   819
387   828
388   835
389   841
390   851
391   861
392   867
393   873
394   877
395   887
396   896
397   907
398   915
399   923
400   932
401    87
402   142
403   179
404   209
405   229
406   257
407   280
408   306
409   325
410   341
411   357
412   374
413   389
414   402
415   411
416   419
417   436
418   449
419   462
420   469
421   484
422   502
423   508
424   525
425   535
426   547
427   557
428   568
429   579
430   590
431   600
432   611
433   627
434   637
435   643
436   651
437   657
438   668
439   676
440   685
441   693
442   703
443   713
444   721
445   726
446   731
447   734
448   746
449   752
450   759
451   770
452   779
453   789
454   797
455   803
456   812
457   818
458   827
459   834
460   839
461   848
462   861
463   871
464   876
465   880
466   886
467   894
468   908
469   912
470   919
471   924
472   931
473   936
474   945
475   948
476   956
477   967
478   975
479   981
480   985
481  1002
482  1006
483  1014
484  1023
485  1030
486  1035
487  1048
488  1057
489  1064
490  1075
491  1085
492  1091
493  1097
494  1107
495  1120
496  1131
497  1143
498  1153
499  1164
500  1173
enrichment.plotter(gene.hic.filt, "min_FDR.C", "adj.P.Val", "Minimum FDR of Hi-C Contacts Overlapping Gene, Chimp")
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp    chisq.p Dneither   DE DHiC
1   0.010    0.01 0.03719912 0.04602134 0.41639016     6981  440  341
2   0.010    0.02 0.05470460 0.06029053 0.67753993     6878  432  444
3   0.010    0.03 0.06345733 0.06877491 0.71307165     6816  428  506
4   0.010    0.04 0.07658643 0.08073017 0.80516417     6729  422  593
5   0.010    0.05 0.08533917 0.09114282 0.71842910     6652  418  670
6   0.010    0.06 0.10284464 0.10309808 1.00000000     6567  410  755
7   0.010    0.07 0.11816193 0.11261088 0.75605305     6500  403  822
8   0.010    0.08 0.13566740 0.12366628 0.46536133     6422  395  900
9   0.010    0.09 0.15098468 0.13793547 0.44491130     6318  388 1004
10  0.010    0.10 0.17286652 0.14924798 0.16366582     6240  378 1082
11  0.010    0.11 0.18161926 0.15953207 0.20649139     6164  374 1158
12  0.010    0.12 0.19474836 0.17380126 0.24832927     6059  368 1263
13  0.010    0.13 0.19912473 0.18524232 0.46825115     5972  366 1350
14  0.010    0.14 0.21006565 0.19822599 0.55256566     5876  361 1446
15  0.010    0.15 0.22757112 0.21262373 0.45564427     5772  353 1550
16  0.010    0.16 0.23632385 0.22355058 0.53677763     5691  349 1631
17  0.010    0.17 0.25601751 0.24051935 0.45772189     5568  340 1754
18  0.010    0.18 0.26914661 0.25388867 0.47332973     5470  334 1852
19  0.010    0.19 0.27789934 0.26828641 0.67181507     5362  330 1960
20  0.010    0.20 0.29321663 0.28486952 0.72327476     5240  323 2082
21  0.010    0.21 0.30415755 0.29605348 0.73509898     5158  318 2164
22  0.010    0.22 0.32822757 0.31302224 0.50252673     5037  307 2285
23  0.010    0.23 0.35010941 0.32536316 0.26597090     4951  297 2371
24  0.010    0.24 0.37417943 0.34156061 0.14298807     4836  286 2486
25  0.010    0.25 0.38512035 0.35878648 0.24625179     4707  281 2615
26  0.010    0.26 0.40043764 0.37652655 0.29942638     4576  274 2746
27  0.010    0.27 0.42013129 0.39400951 0.25906713     4449  265 2873
28  0.010    0.28 0.43326039 0.41136393 0.35159652     4320  259 3002
29  0.010    0.29 0.44201313 0.42666152 0.52530646     4205  255 3117
30  0.010    0.30 0.46170678 0.44375884 0.45477419     4081  246 3241
31  0.010    0.31 0.47264770 0.45879933 0.57276175     3969  241 3353
32  0.010    0.32 0.48140044 0.47229721 0.72371427     3868  237 3454
33  0.010    0.33 0.49890591 0.49157989 0.78356615     3726  229 3596
34  0.010    0.34 0.50765864 0.50803445 1.00000000     3602  225 3720
35  0.010    0.35 0.51641138 0.52230364 0.83237068     3495  221 3827
36  0.010    0.36 0.53391685 0.53451600 1.00000000     3408  213 3914
37  0.010    0.37 0.55798687 0.54968505 0.74956060     3301  202 4021
38  0.010    0.38 0.56673961 0.56742512 1.00000000     3167  198 4155
39  0.010    0.39 0.59080963 0.58645070 0.88385923     3030  187 4292
40  0.010    0.40 0.60612691 0.60264816 0.91448948     2911  180 4411
41  0.010    0.41 0.61925602 0.61588893 0.91798432     2814  174 4508
42  0.010    0.42 0.63894967 0.63092943 0.75180079     2706  165 4616
43  0.010    0.43 0.64332604 0.64622702 0.93363786     2589  163 4733
44  0.010    0.44 0.65645514 0.65972490 0.91940643     2490  157 4832
45  0.010    0.45 0.67177243 0.67630801 0.87124764     2368  150 4954
46  0.010    0.46 0.67614880 0.68903458 0.57458454     2271  148 5051
47  0.010    0.47 0.68927790 0.70111840 0.60496292     2183  142 5139
48  0.010    0.48 0.70240700 0.71294511 0.64552123     2097  136 5225
49  0.010    0.49 0.72866521 0.72310066 0.82576289     2030  124 5292
50  0.010    0.50 0.73522976 0.73415606 1.00000000     1947  121 5375
51  0.010    0.51 0.74398249 0.74238334 0.97969782     1887  117 5435
52  0.010    0.52 0.76148796 0.75408150 0.74670064     1804  109 5518
53  0.010    0.53 0.76805252 0.76385139 0.87193928     1731  106 5591
54  0.010    0.54 0.76805252 0.77143592 0.90437926     1672  106 5650
55  0.010    0.55 0.77242888 0.78133436 0.67710768     1597  104 5725
56  0.010    0.56 0.78118162 0.78891888 0.71981431     1542  100 5780
57  0.010    0.57 0.78555799 0.79637486 0.59471808     1486   98 5836
58  0.010    0.58 0.80087527 0.80460213 0.88367846     1429   91 5893
59  0.010    0.59 0.80525164 0.81218666 0.74175482     1372   89 5950
60  0.010    0.60 0.81400438 0.81951408 0.80027936     1319   85 6003
61  0.010    0.61 0.81400438 0.82529888 0.55389831     1274   85 6048
62  0.010    0.62 0.82932166 0.83185499 0.93242404     1230   78 6092
63  0.010    0.63 0.83150985 0.83879676 0.71057101     1177   77 6145
64  0.010    0.64 0.84682713 0.84560998 0.99401196     1131   70 6191
65  0.010    0.65 0.85557987 0.85229464 0.89176115     1083   66 6239
66  0.010    0.66 0.85995624 0.85936496 1.00000000     1030   64 6292
67  0.010    0.67 0.86870897 0.86502121 0.86717112      990   60 6332
68  0.010    0.68 0.87308534 0.86913485 0.85195524      960   58 6362
69  0.010    0.69 0.87527352 0.87401980 0.99154232      923   57 6399
70  0.010    0.70 0.89059081 0.88031881 0.53325817      881   50 6441
71  0.010    0.71 0.89277899 0.88520375 0.65415798      844   49 6478
72  0.010    0.72 0.89934354 0.89137421 0.62636358      799   46 6523
73  0.010    0.73 0.89934354 0.89535930 0.83518651      768   46 6554
74  0.010    0.74 0.90371991 0.89973004 0.83176661      736   44 6586
75  0.010    0.75 0.90590810 0.90448644 0.98040851      700   43 6622
76  0.010    0.76 0.91028446 0.90847153 0.95619447      671   41 6651
77  0.010    0.77 0.91028446 0.91399923 0.83681809      628   41 6694
78  0.010    0.78 0.91903720 0.91862707 1.00000000      596   37 6726
79  0.010    0.79 0.92341357 0.92248361 1.00000000      568   35 6754
80  0.010    0.80 0.92560175 0.92646870 1.00000000      538   34 6784
81  0.010    0.81 0.92778993 0.92929682 0.97169289      517   33 6805
82  0.010    0.82 0.93435449 0.93366757 1.00000000      486   30 6836
83  0.010    0.83 0.94091904 0.93906672 0.94431784      447   27 6875
84  0.010    0.84 0.94310722 0.94215195 1.00000000      424   26 6898
85  0.010    0.85 0.94748359 0.94575138 0.95050261      398   24 6924
86  0.010    0.86 0.95404814 0.95037923 0.79389239      365   21 6957
87  0.010    0.87 0.95623632 0.95410721 0.91321112      337   20 6985
88  0.010    0.88 0.96061269 0.95834940 0.89739744      306   18 7016
89  0.010    0.89 0.96280088 0.96143463 0.97515567      283   17 7039
90  0.010    0.90 0.96717724 0.96490551 0.88786089      258   15 7064
91  0.010    0.91 0.97155361 0.96734799 0.69966413      241   13 7081
92  0.010    0.92 0.97155361 0.97159018 1.00000000      208   13 7114
93  0.010    0.93 0.97592998 0.97544672 1.00000000      180   11 7142
94  0.010    0.94 0.97592998 0.97827484 0.85005538      158   11 7164
95  0.010    0.95 0.98468271 0.98213138 0.80848152      132    7 7190
96  0.010    0.96 0.98905908 0.98624502 0.74488621      102    5 7220
97  0.010    0.97 0.99124726 0.99010156 0.99083340       73    4 7249
98  0.010    0.98 0.99124726 0.99305823 0.84911228       50    4 7272
99  0.010    0.99 0.99781182 0.99652912 0.94366508       26    1 7296
100 0.010    1.00 1.00000000 1.00000000 0.00000000        0    0 7322
101 0.025    0.01 0.03913043 0.04602134 0.32781229     6537  884  322
102 0.025    0.02 0.05652174 0.06029053 0.66160468     6442  868  417
103 0.025    0.03 0.06304348 0.06877491 0.50785313     6382  862  477
104 0.025    0.04 0.07608696 0.08073017 0.62688337     6301  850  558
105 0.025    0.05 0.08695652 0.09114282 0.68265658     6230  840  629
106 0.025    0.06 0.10217391 0.10309808 0.96774296     6151  826  708
107 0.025    0.07 0.11521739 0.11261088 0.83303776     6089  814  770
108 0.025    0.08 0.13152174 0.12366628 0.47308799     6018  799  841
109 0.025    0.09 0.14782609 0.13793547 0.38125784     5922  784  937
110 0.025    0.10 0.16521739 0.14924798 0.16200280     5850  768 1009
111 0.025    0.11 0.17500000 0.15953207 0.18798773     5779  759 1080
112 0.025    0.12 0.19021739 0.17380126 0.17604726     5682  745 1177
113 0.025    0.13 0.19565217 0.18524232 0.41201708     5598  740 1261
114 0.025    0.14 0.20978261 0.19822599 0.37221093     5510  727 1349
115 0.025    0.15 0.22500000 0.21262373 0.35022769     5412  713 1447
116 0.025    0.16 0.23152174 0.22355058 0.56469463     5333  707 1526
117 0.025    0.17 0.25108696 0.24051935 0.44869172     5219  689 1640
118 0.025    0.18 0.26739130 0.25388867 0.33615708     5130  674 1729
119 0.025    0.19 0.28152174 0.26828641 0.35481229     5031  661 1828
120 0.025    0.20 0.29565217 0.28486952 0.46369146     4915  648 1944
121 0.025    0.21 0.30434783 0.29605348 0.58339689     4836  640 2023
122 0.025    0.22 0.31956522 0.31302224 0.67601381     4718  626 2141
123 0.025    0.23 0.33586957 0.32536316 0.49214601     4637  611 2222
124 0.025    0.24 0.35434783 0.34156061 0.40430099     4528  594 2331
125 0.025    0.25 0.36847826 0.35878648 0.53783272     4407  581 2452
126 0.025    0.26 0.38586957 0.37652655 0.55743919     4285  565 2574
127 0.025    0.27 0.40108696 0.39400951 0.66579041     4163  551 2696
128 0.025    0.28 0.41630435 0.41136393 0.77286554     4042  537 2817
129 0.025    0.29 0.42608696 0.42666152 0.99837992     3932  528 2927
130 0.025    0.30 0.44347826 0.44375884 1.00000000     3815  512 3044
131 0.025    0.31 0.46304348 0.45879933 0.81041430     3716  494 3143
132 0.025    0.32 0.46956522 0.47229721 0.88739359     3617  488 3242
133 0.025    0.33 0.49021739 0.49157989 0.95779620     3486  469 3373
134 0.025    0.34 0.50217391 0.50803445 0.73118883     3369  458 3490
135 0.025    0.35 0.50978261 0.52230364 0.43859878     3265  451 3594
136 0.025    0.36 0.52500000 0.53451600 0.56121225     3184  437 3675
137 0.025    0.37 0.54565217 0.54968505 0.82077505     3085  418 3774
138 0.025    0.38 0.55326087 0.56742512 0.37450864     2954  411 3905
139 0.025    0.39 0.57934783 0.58645070 0.66702173     2830  387 4029
140 0.025    0.40 0.59673913 0.60264816 0.72320656     2720  371 4139
141 0.025    0.41 0.60978261 0.61588893 0.71180054     2629  359 4230
142 0.025    0.42 0.63260870 0.63092943 0.93939605     2533  338 4326
143 0.025    0.43 0.64347826 0.64622702 0.88156759     2424  328 4435
144 0.025    0.44 0.65652174 0.65972490 0.85611214     2331  316 4528
145 0.025    0.45 0.66956522 0.67630801 0.66866048     2214  304 4645
146 0.025    0.46 0.67500000 0.68903458 0.34647540     2120  299 4739
147 0.025    0.47 0.68478261 0.70111840 0.26512452     2035  290 4824
148 0.025    0.48 0.70000000 0.71294511 0.37588142     1957  276 4902
149 0.025    0.49 0.71630435 0.72310066 0.65171620     1893  261 4966
150 0.025    0.50 0.72826087 0.73415606 0.69557495     1818  250 5041
151 0.025    0.51 0.73586957 0.74238334 0.65922651     1761  243 5098
152 0.025    0.52 0.74891304 0.75408150 0.72865073     1682  231 5177
153 0.025    0.53 0.75434783 0.76385139 0.49558018     1611  226 5248
154 0.025    0.54 0.75978261 0.77143592 0.39275518     1557  221 5302
155 0.025    0.55 0.76956522 0.78133436 0.38034493     1489  212 5370
156 0.025    0.56 0.77500000 0.78891888 0.28971578     1435  207 5424
157 0.025    0.57 0.77826087 0.79637486 0.15871600     1380  204 5479
158 0.025    0.58 0.78804348 0.80460213 0.19199912     1325  195 5534
159 0.025    0.59 0.79565217 0.81218666 0.18598721     1273  188 5586
160 0.025    0.60 0.81086957 0.81951408 0.49624962     1230  174 5629
161 0.025    0.61 0.81304348 0.82529888 0.31909317     1187  172 5672
162 0.025    0.62 0.82500000 0.83185499 0.58566998     1147  161 5712
163 0.025    0.63 0.82826087 0.83879676 0.38006880     1096  158 5763
164 0.025    0.64 0.83913043 0.84560998 0.59564353     1053  148 5806
165 0.025    0.65 0.84673913 0.85229464 0.64817755     1008  141 5851
166 0.025    0.66 0.85434783 0.85936496 0.67764913      960  134 5899
167 0.025    0.67 0.85869565 0.86502121 0.58465896      920  130 5939
168 0.025    0.68 0.86739130 0.86913485 0.90849177      896  122 5963
169 0.025    0.69 0.87173913 0.87401980 0.86571282      862  118 5997
170 0.025    0.70 0.88478261 0.88031881 0.69643710      825  106 6034
171 0.025    0.71 0.88804348 0.88520375 0.81601017      790  103 6069
172 0.025    0.72 0.89347826 0.89137421 0.87130670      747   98 6112
173 0.025    0.73 0.89673913 0.89535930 0.92966982      719   95 6140
174 0.025    0.74 0.90108696 0.89973004 0.93029024      689   91 6170
175 0.025    0.75 0.90326087 0.90448644 0.94024599      654   89 6205
176 0.025    0.76 0.90869565 0.90847153 1.00000000      628   84 6231
177 0.025    0.77 0.91521739 0.91399923 0.93804094      591   78 6268
178 0.025    0.78 0.92065217 0.91862707 0.86104309      560   73 6299
179 0.025    0.79 0.92282609 0.92248361 1.00000000      532   71 6327
180 0.025    0.80 0.92391304 0.92646870 0.80334281      502   70 6357
181 0.025    0.81 0.92500000 0.92929682 0.63622388      481   69 6378
182 0.025    0.82 0.93043478 0.93366757 0.72704042      452   64 6407
183 0.025    0.83 0.93586957 0.93906672 0.72008749      415   59 6444
184 0.025    0.84 0.93913043 0.94215195 0.73169720      394   56 6465
185 0.025    0.85 0.94565217 0.94575138 1.00000000      372   50 6487
186 0.025    0.86 0.95108696 0.95037923 0.98050815      341   45 6518
187 0.025    0.87 0.95217391 0.95410721 0.83012405      313   44 6546
188 0.025    0.88 0.95760870 0.95834940 0.97456167      285   39 6574
189 0.025    0.89 0.95978261 0.96143463 0.85247597      263   37 6596
190 0.025    0.90 0.96521739 0.96490551 1.00000000      241   32 6618
191 0.025    0.91 0.96956522 0.96734799 0.76096982      226   28 6633
192 0.025    0.92 0.97282609 0.97159018 0.89290843      196   25 6663
193 0.025    0.93 0.97608696 0.97544672 0.98388659      169   22 6690
194 0.025    0.94 0.97717391 0.97827484 0.90169915      148   21 6711
195 0.025    0.95 0.98478261 0.98213138 0.60729229      125   14 6734
196 0.025    0.96 0.99021739 0.98624502 0.34163041       98    9 6761
197 0.025    0.97 0.99239130 0.99010156 0.56882123       70    7 6789
198 0.025    0.98 0.99456522 0.99305823 0.70777222       49    5 6810
199 0.025    0.99 0.99782609 0.99652912 0.67898675       25    2 6834
200 0.025    1.00 1.00000000 1.00000000 0.00000000        0    0 6859
201 0.050    0.01 0.04581246 0.04602134 1.00000000     6088 1333  294
202 0.050    0.02 0.06227631 0.06029053 0.77777856     6000 1310  382
203 0.050    0.03 0.06871868 0.06877491 1.00000000     5943 1301  439
204 0.050    0.04 0.08231926 0.08073017 0.85205836     5869 1282  513
205 0.050    0.05 0.09234073 0.09114282 0.90413875     5802 1268  580
206 0.050    0.06 0.10522548 0.10309808 0.81023578     5727 1250  655
207 0.050    0.07 0.11596278 0.11261088 0.69592474     5668 1235  714
208 0.050    0.08 0.13171081 0.12366628 0.33529126     5604 1213  778
209 0.050    0.09 0.14745884 0.13793547 0.27272794     5515 1191  867
210 0.050    0.10 0.16392269 0.14924798 0.09732703     5450 1168  932
211 0.050    0.11 0.17465999 0.15953207 0.09601724     5385 1153  997
212 0.050    0.12 0.19112384 0.17380126 0.06469081     5297 1130 1085
213 0.050    0.13 0.19613457 0.18524232 0.26316783     5215 1123 1167
214 0.050    0.14 0.21188261 0.19822599 0.16865859     5136 1101 1246
215 0.050    0.15 0.22691482 0.21262373 0.15996501     5045 1080 1337
216 0.050    0.16 0.23622047 0.22355058 0.22267235     4973 1067 1409
217 0.050    0.17 0.25411596 0.24051935 0.20118405     4866 1042 1516
218 0.050    0.18 0.27129563 0.25388867 0.10600020     4786 1018 1596
219 0.050    0.19 0.28489621 0.26828641 0.13012344     4693  999 1689
220 0.050    0.20 0.29849678 0.28486952 0.22507125     4583  980 1799
221 0.050    0.21 0.30708661 0.29605348 0.33457088     4508  968 1874
222 0.050    0.22 0.32498210 0.31302224 0.30187815     4401  943 1981
223 0.050    0.23 0.33858268 0.32536316 0.25729324     4324  924 2058
224 0.050    0.24 0.36148890 0.34156061 0.08858673     4230  892 2152
225 0.050    0.25 0.37652112 0.35878648 0.13492415     4117  871 2265
226 0.050    0.26 0.39155333 0.37652655 0.21155020     4000  850 2382
227 0.050    0.27 0.40300644 0.39400951 0.46566032     3880  834 2502
228 0.050    0.28 0.42233357 0.41136393 0.37353028     3772  807 2610
229 0.050    0.29 0.43235505 0.42666152 0.65620226     3667  793 2715
230 0.050    0.30 0.44881890 0.44375884 0.69613225     3557  770 2825
231 0.050    0.31 0.46886185 0.45879933 0.42159692     3468  742 2914
232 0.050    0.32 0.47745168 0.47229721 0.69175899     3375  730 3007
233 0.050    0.33 0.49964209 0.49157989 0.52482554     3256  699 3126
234 0.050    0.34 0.51610594 0.50803445 0.52433089     3151  676 3231
235 0.050    0.35 0.52684324 0.52230364 0.72974976     3055  661 3327
236 0.050    0.36 0.54187545 0.53451600 0.56244205     2981  640 3401
237 0.050    0.37 0.56335004 0.54968505 0.26972533     2893  610 3489
238 0.050    0.38 0.57337151 0.56742512 0.64159576     2769  596 3613
239 0.050    0.39 0.59914102 0.58645070 0.30143717     2657  560 3725
240 0.050    0.40 0.61417323 0.60264816 0.34635464     2552  539 3830
241 0.050    0.41 0.62705798 0.61588893 0.35902732     2467  521 3915
242 0.050    0.42 0.64495347 0.63092943 0.24254697     2375  496 4007
243 0.050    0.43 0.65783822 0.64622702 0.33145117     2274  478 4108
244 0.050    0.44 0.67215462 0.65972490 0.29308662     2189  458 4193
245 0.050    0.45 0.68217609 0.67630801 0.62698905     2074  444 4308
246 0.050    0.46 0.69005011 0.68903458 0.95325128     1986  433 4396
247 0.050    0.47 0.69935576 0.70111840 0.89923541     1905  420 4477
248 0.050    0.48 0.71224052 0.71294511 0.97477263     1831  402 4551
249 0.050    0.49 0.72512527 0.72310066 0.87784469     1770  384 4612
250 0.050    0.50 0.73586256 0.73415606 0.89975855     1699  369 4683
251 0.050    0.51 0.74373658 0.74238334 0.92517458     1646  358 4736
252 0.050    0.52 0.75590551 0.75408150 0.88827406     1572  341 4810
253 0.050    0.53 0.76234789 0.76385139 0.91137416     1505  332 4877
254 0.050    0.54 0.76950608 0.77143592 0.87723499     1456  322 4926
255 0.050    0.55 0.77952756 0.78133436 0.88498964     1393  308 4989
256 0.050    0.56 0.78668576 0.78891888 0.84960393     1344  298 5038
257 0.050    0.57 0.79169649 0.79637486 0.65796284     1293  291 5089
258 0.050    0.58 0.79957051 0.80460213 0.62668364     1240  280 5142
259 0.050    0.59 0.80529707 0.81218666 0.49012780     1189  272 5193
260 0.050    0.60 0.82176092 0.81951408 0.83938997     1155  249 5227
261 0.050    0.61 0.82605583 0.82529888 0.96540994     1116  243 5266
262 0.050    0.62 0.83536149 0.83185499 0.72828994     1078  230 5304
263 0.050    0.63 0.84037223 0.83879676 0.89132096     1031  223 5351
264 0.050    0.64 0.84896206 0.84560998 0.73238747      990  211 5392
265 0.050    0.65 0.85468862 0.85229464 0.81281215      946  203 5436
266 0.050    0.66 0.86041518 0.85936496 0.93450663      899  195 5483
267 0.050    0.67 0.86542591 0.86502121 0.99549138      862  188 5520
268 0.050    0.68 0.87115247 0.86913485 0.83907578      838  180 5544
269 0.050    0.69 0.87544739 0.87401980 0.89417585      806  174 5576
270 0.050    0.70 0.88833214 0.88031881 0.33043625      775  156 5607
271 0.050    0.71 0.89119542 0.88520375 0.46583051      741  152 5641
272 0.050    0.72 0.89549034 0.89137421 0.61821131      699  146 5683
273 0.050    0.73 0.89835361 0.89535930 0.72227321      672  142 5710
274 0.050    0.74 0.90264853 0.89973004 0.72499875      644  136 5738
275 0.050    0.75 0.90622763 0.90448644 0.84601580      612  131 5770
276 0.050    0.76 0.91195419 0.90847153 0.65475917      589  123 5793
277 0.050    0.77 0.91982820 0.91399923 0.42067679      557  112 5825
278 0.050    0.78 0.92483894 0.91862707 0.37694955      528  105 5854
279 0.050    0.79 0.92770222 0.92248361 0.45320988      502  101 5880
280 0.050    0.80 0.92841804 0.92646870 0.80134695      472  100 5910
281 0.050    0.81 0.92984968 0.92929682 0.97496417      452   98 5930
282 0.050    0.82 0.93486042 0.93366757 0.88988874      425   91 5957
283 0.050    0.83 0.93915533 0.93906672 1.00000000      389   85 5993
284 0.050    0.84 0.94273443 0.94215195 0.96833631      370   80 6012
285 0.050    0.85 0.94917681 0.94575138 0.57627253      351   71 6031
286 0.050    0.86 0.95490336 0.95037923 0.42855275      323   63 6059
287 0.050    0.87 0.95705082 0.95410721 0.61011800      297   60 6085
288 0.050    0.88 0.96206156 0.95834940 0.48843860      271   53 6111
289 0.050    0.89 0.96492484 0.96143463 0.50205955      251   49 6131
290 0.050    0.90 0.96921976 0.96490551 0.37498108      230   43 6152
291 0.050    0.91 0.97208304 0.96734799 0.30948257      215   39 6167
292 0.050    0.92 0.97637795 0.97159018 0.27121778      188   33 6194
293 0.050    0.93 0.97995705 0.97544672 0.26820649      163   28 6219
294 0.050    0.94 0.98138869 0.97827484 0.43534375      143   26 6239
295 0.050    0.95 0.98711525 0.98213138 0.14959493      121   18 6261
296 0.050    0.96 0.99212598 0.98624502 0.05037509       96   11 6286
297 0.050    0.97 0.99427344 0.99010156 0.11188484       69    8 6313
298 0.050    0.98 0.99570508 0.99305823 0.25528324       48    6 6334
299 0.050    0.99 0.99856836 0.99652912 0.23812048       25    2 6357
300 0.050    1.00 1.00000000 1.00000000 0.00000000        0    0 6382
301 0.075    0.01 0.04745763 0.04602134 0.79209553     5735 1686  274
302 0.075    0.02 0.06384181 0.06029053 0.51093910     5653 1657  356
303 0.075    0.03 0.07175141 0.06877491 0.61035110     5601 1643  408
304 0.075    0.04 0.08361582 0.08073017 0.64737367     5529 1622  480
305 0.075    0.05 0.09265537 0.09114282 0.83789961     5464 1606  545
306 0.075    0.06 0.10621469 0.10309808 0.65549869     5395 1582  614
307 0.075    0.07 0.11751412 0.11261088 0.48411265     5341 1562  668
308 0.075    0.08 0.13276836 0.12366628 0.19968981     5282 1535  727
309 0.075    0.09 0.14971751 0.13793547 0.11041666     5201 1505  808
310 0.075    0.10 0.16384181 0.14924798 0.05453962     5138 1480  871
311 0.075    0.11 0.17231638 0.15953207 0.10219235     5073 1465  936
312 0.075    0.12 0.18757062 0.17380126 0.08843940     4989 1438 1020
313 0.075    0.13 0.19209040 0.18524232 0.41852763     4908 1430 1101
314 0.075    0.14 0.20734463 0.19822599 0.28870210     4834 1403 1175
315 0.075    0.15 0.21920904 0.21262373 0.46089733     4743 1382 1266
316 0.075    0.16 0.23107345 0.22355058 0.40547307     4679 1361 1330
317 0.075    0.17 0.24915254 0.24051935 0.34964870     4579 1329 1430
318 0.075    0.18 0.26440678 0.25388867 0.26027563     4502 1302 1507
319 0.075    0.19 0.27966102 0.26828641 0.23077182     4417 1275 1592
320 0.075    0.20 0.29322034 0.28486952 0.39217024     4312 1251 1697
321 0.075    0.21 0.30451977 0.29605348 0.39082614     4245 1231 1764
322 0.075    0.22 0.32316384 0.31302224 0.30881307     4146 1198 1863
323 0.075    0.23 0.33841808 0.32536316 0.19190162     4077 1171 1932
324 0.075    0.24 0.36214689 0.34156061 0.04042020     3993 1129 2016
325 0.075    0.25 0.37570621 0.35878648 0.09683637     3883 1105 2126
326 0.075    0.26 0.38983051 0.37652655 0.19827783     3770 1080 2239
327 0.075    0.27 0.40395480 0.39400951 0.34384508     3659 1055 2350
328 0.075    0.28 0.42259887 0.41136393 0.28668421     3557 1022 2452
329 0.075    0.29 0.43502825 0.42666152 0.43396854     3460 1000 2549
330 0.075    0.30 0.45141243 0.44375884 0.47758589     3356  971 2653
331 0.075    0.31 0.47118644 0.45879933 0.24490727     3274  936 2735
332 0.075    0.32 0.47909605 0.47229721 0.53209446     3183  922 2826
333 0.075    0.33 0.50282486 0.49157989 0.29387546     3075  880 2934
334 0.075    0.34 0.51864407 0.50803445 0.32275579     2975  852 3034
335 0.075    0.35 0.53050847 0.52230364 0.44772478     2885  831 3124
336 0.075    0.36 0.54632768 0.53451600 0.26855185     2818  803 3191
337 0.075    0.37 0.56723164 0.54968505 0.09670833     2737  766 3272
338 0.075    0.38 0.57740113 0.56742512 0.34897536     2617  748 3392
339 0.075    0.39 0.60112994 0.58645070 0.16170193     2511  706 3498
340 0.075    0.40 0.61751412 0.60264816 0.15370761     2414  677 3595
341 0.075    0.41 0.62768362 0.61588893 0.25721847     2329  659 3680
342 0.075    0.42 0.64293785 0.63092943 0.24475308     2239  632 3770
343 0.075    0.43 0.65649718 0.64622702 0.31735885     2144  608 3865
344 0.075    0.44 0.67175141 0.65972490 0.23542473     2066  581 3943
345 0.075    0.45 0.68361582 0.67630801 0.47229730     1958  560 4051
346 0.075    0.46 0.69322034 0.68903458 0.68647366     1876  543 4133
347 0.075    0.47 0.70338983 0.70111840 0.83524301     1800  525 4209
348 0.075    0.48 0.71694915 0.71294511 0.69373809     1732  501 4277
349 0.075    0.49 0.73107345 0.72310066 0.41069032     1678  476 4331
350 0.075    0.50 0.74067797 0.73415606 0.49900378     1609  459 4400
351 0.075    0.51 0.74745763 0.74238334 0.59993110     1557  447 4452
352 0.075    0.52 0.76214689 0.75408150 0.38696411     1492  421 4517
353 0.075    0.53 0.76949153 0.76385139 0.54594788     1429  408 4580
354 0.075    0.54 0.77683616 0.77143592 0.55961812     1383  395 4626
355 0.075    0.55 0.78644068 0.78133436 0.57640859     1323  378 4686
356 0.075    0.56 0.79322034 0.78891888 0.63733061     1276  366 4733
357 0.075    0.57 0.79943503 0.79637486 0.74126081     1229  355 4780
358 0.075    0.58 0.80847458 0.80460213 0.66472624     1181  339 4828
359 0.075    0.59 0.81468927 0.81218666 0.78554281     1133  328 4876
360 0.075    0.60 0.82881356 0.81951408 0.26173435     1101  303 4908
361 0.075    0.61 0.83446328 0.82529888 0.26284316     1066  293 4943
362 0.075    0.62 0.84237288 0.83185499 0.19018033     1029  279 4980
363 0.075    0.63 0.84915254 0.83879676 0.18975470      987  267 5022
364 0.075    0.64 0.85649718 0.84560998 0.16004497      947  254 5062
365 0.075    0.65 0.86214689 0.85229464 0.19667322      905  244 5104
366 0.075    0.66 0.86779661 0.85936496 0.26182707      860  234 5149
367 0.075    0.67 0.87231638 0.86502121 0.32590572      824  226 5185
368 0.075    0.68 0.87683616 0.86913485 0.29234275      800  218 5209
369 0.075    0.69 0.88248588 0.87401980 0.23778665      772  208 5237
370 0.075    0.70 0.89322034 0.88031881 0.06274743      742  189 5267
371 0.075    0.71 0.89717514 0.88520375 0.07921885      711  182 5298
372 0.075    0.72 0.90056497 0.89137421 0.17056493      669  176 5340
373 0.075    0.73 0.90282486 0.89535930 0.26129594      642  172 5367
374 0.075    0.74 0.90734463 0.89973004 0.24259883      616  164 5393
375 0.075    0.75 0.91129944 0.90448644 0.28752912      586  157 5423
376 0.075    0.76 0.91581921 0.90847153 0.24086087      563  149 5446
377 0.075    0.77 0.92429379 0.91399923 0.08737430      535  134 5474
378 0.075    0.78 0.92881356 0.91862707 0.08291851      507  126 5502
379 0.075    0.79 0.93163842 0.92248361 0.11223827      482  121 5527
380 0.075    0.80 0.93220339 0.92646870 0.31734596      452  120 5557
381 0.075    0.81 0.93389831 0.92929682 0.41992356      433  117 5576
382 0.075    0.82 0.93785311 0.93366757 0.45280558      406  110 5603
383 0.075    0.83 0.94350282 0.93906672 0.40586797      374  100 5635
384 0.075    0.84 0.94689266 0.94215195 0.36065264      356   94 5653
385 0.075    0.85 0.95254237 0.94575138 0.16899097      338   84 5671
386 0.075    0.86 0.95706215 0.95037923 0.15829285      310   76 5699
387 0.075    0.87 0.95932203 0.95410721 0.25918809      285   72 5724
388 0.075    0.88 0.96384181 0.95834940 0.21193497      260   64 5749
389 0.075    0.89 0.96610169 0.96143463 0.27572417      240   60 5769
390 0.075    0.90 0.97005650 0.96490551 0.20535996      220   53 5789
391 0.075    0.91 0.97288136 0.96734799 0.15728169      206   48 5803
392 0.075    0.92 0.97683616 0.97159018 0.15269525      180   41 5829
393 0.075    0.93 0.98079096 0.97544672 0.11743258      157   34 5852
394 0.075    0.94 0.98192090 0.97827484 0.26940831      137   32 5872
395 0.075    0.95 0.98644068 0.98213138 0.14565484      115   24 5894
396 0.075    0.96 0.99096045 0.98624502 0.06847458       91   16 5918
397 0.075    0.97 0.99378531 0.99010156 0.10004857       66   11 5943
398 0.075    0.98 0.99491525 0.99305823 0.36399814       45    9 5964
399 0.075    0.99 0.99830508 0.99652912 0.22414616       24    3 5985
400 0.075    1.00 1.00000000 1.00000000 0.00000000        0    0 6009
401 0.100    0.01 0.04780115 0.04602134 0.69404773     5429 1992  258
402 0.100    0.02 0.06309751 0.06029053 0.56385322     5350 1960  337
403 0.100    0.03 0.07170172 0.06877491 0.56993840     5302 1942  385
404 0.100    0.04 0.08365201 0.08073017 0.59832472     5234 1917  453
405 0.100    0.05 0.09273423 0.09114282 0.80153540     5172 1898  515
406 0.100    0.06 0.10611855 0.10309808 0.62462900     5107 1870  580
407 0.100    0.07 0.11663480 0.11261088 0.52185598     5055 1848  632
408 0.100    0.08 0.13145315 0.12366628 0.22001328     5000 1817  687
409 0.100    0.09 0.14866157 0.13793547 0.10376822     4925 1781  762
410 0.100    0.10 0.16252390 0.14924798 0.05033181     4866 1752  821
411 0.100    0.11 0.17112811 0.15953207 0.09708898     4804 1734  883
412 0.100    0.12 0.18785851 0.17380126 0.05109556     4728 1699  959
413 0.100    0.13 0.19407266 0.18524232 0.23681716     4652 1686 1035
414 0.100    0.14 0.20889101 0.19822599 0.16181739     4582 1655 1105
415 0.100    0.15 0.22179732 0.21262373 0.24276802     4497 1628 1190
416 0.100    0.16 0.23470363 0.22355058 0.16111365     4439 1601 1248
417 0.100    0.17 0.25191205 0.24051935 0.16271351     4343 1565 1344
418 0.100    0.18 0.26529637 0.25388867 0.16984159     4267 1537 1420
419 0.100    0.19 0.28107075 0.26828641 0.12986023     4188 1504 1499
420 0.100    0.20 0.29541109 0.28486952 0.22206993     4089 1474 1598
421 0.100    0.21 0.30544933 0.29605348 0.28327947     4023 1453 1664
422 0.100    0.22 0.32456979 0.31302224 0.19205824     3931 1413 1756
423 0.100    0.23 0.34130019 0.32536316 0.07307415     3870 1378 1817
424 0.100    0.24 0.36424474 0.34156061 0.01134750     3792 1330 1895
425 0.100    0.25 0.37715105 0.35878648 0.04322820     3685 1303 2002
426 0.100    0.26 0.39244742 0.37652655 0.08338422     3579 1271 2108
427 0.100    0.27 0.40917782 0.39400951 0.10217805     3478 1236 2209
428 0.100    0.28 0.42782027 0.41136393 0.07790617     3382 1197 2305
429 0.100    0.29 0.43929254 0.42666152 0.18015419     3287 1173 2400
430 0.100    0.30 0.45506692 0.44375884 0.23333525     3187 1140 2500
431 0.100    0.31 0.47418738 0.45879933 0.10388975     3110 1100 2577
432 0.100    0.32 0.48374761 0.47229721 0.22962750     3025 1080 2662
433 0.100    0.33 0.50621415 0.49157989 0.12348158     2922 1033 2765
434 0.100    0.34 0.51959847 0.50803445 0.22559435     2822 1005 2865
435 0.100    0.35 0.53202677 0.52230364 0.30977736     2737  979 2950
436 0.100    0.36 0.54636711 0.53451600 0.21301597     2672  949 3015
437 0.100    0.37 0.56453155 0.54968505 0.11627889     2592  911 3095
438 0.100    0.38 0.57600382 0.56742512 0.36787312     2478  887 3209
439 0.100    0.39 0.59847036 0.58645070 0.20066824     2377  840 3310
440 0.100    0.40 0.61472275 0.60264816 0.19572995     2285  806 3402
441 0.100    0.41 0.62619503 0.61588893 0.26820810     2206  782 3481
442 0.100    0.42 0.64053537 0.63092943 0.29909594     2119  752 3568
443 0.100    0.43 0.65535373 0.64622702 0.32005652     2031  721 3656
444 0.100    0.44 0.67160612 0.65972490 0.18869885     1960  687 3727
445 0.100    0.45 0.68307839 0.67630801 0.45522222     1855  663 3832
446 0.100    0.46 0.69263862 0.68903458 0.69736569     1776  643 3911
447 0.100    0.47 0.70315488 0.70111840 0.83363022     1704  621 3983
448 0.100    0.48 0.71749522 0.71294511 0.61020852     1642  591 4045
449 0.100    0.49 0.73087954 0.72310066 0.36738932     1591  563 4096
450 0.100    0.50 0.74139579 0.73415606 0.39661108     1527  541 4160
451 0.100    0.51 0.74808795 0.74238334 0.50377799     1477  527 4210
452 0.100    0.52 0.76195029 0.75408150 0.34324055     1415  498 4272
453 0.100    0.53 0.76912046 0.76385139 0.52637824     1354  483 4333
454 0.100    0.54 0.77629063 0.77143592 0.55652485     1310  468 4377
455 0.100    0.55 0.78489484 0.78133436 0.66730060     1251  450 4436
456 0.100    0.56 0.79110899 0.78891888 0.79813324     1205  437 4482
457 0.100    0.57 0.79636711 0.79637486 1.00000000     1158  426 4529
458 0.100    0.58 0.80544933 0.80460213 0.93460514     1113  407 4574
459 0.100    0.59 0.81214149 0.81218666 1.00000000     1068  393 4619
460 0.100    0.60 0.82456979 0.81951408 0.50288069     1037  367 4650
461 0.100    0.61 0.82982792 0.82529888 0.54559312     1003  356 4684
462 0.100    0.62 0.83747610 0.83185499 0.44140894      968  340 4719
463 0.100    0.63 0.84560229 0.83879676 0.33944614      931  323 4756
464 0.100    0.64 0.85277247 0.84560998 0.30535500      893  308 4794
465 0.100    0.65 0.85946463 0.85229464 0.29603789      855  294 4832
466 0.100    0.66 0.86567878 0.85936496 0.34991382      813  281 4874
467 0.100    0.67 0.86998088 0.86502121 0.45989303      778  272 4909
468 0.100    0.68 0.87476099 0.86913485 0.39283718      756  262 4931
469 0.100    0.69 0.88097514 0.87401980 0.27892621      731  249 4956
470 0.100    0.70 0.89005736 0.88031881 0.11745046      701  230 4986
471 0.100    0.71 0.89531549 0.88520375 0.09757324      674  219 5013
472 0.100    0.72 0.89866157 0.89137421 0.22563051      633  212 5054
473 0.100    0.73 0.90105163 0.89535930 0.34056771      607  207 5080
474 0.100    0.74 0.90487572 0.89973004 0.38218960      581  199 5106
475 0.100    0.75 0.90917782 0.90448644 0.41775317      553  190 5134
476 0.100    0.76 0.91347992 0.90847153 0.37628074      531  181 5156
477 0.100    0.77 0.92256214 0.91399923 0.11224190      507  162 5180
478 0.100    0.78 0.92782027 0.91862707 0.07978513      482  151 5205
479 0.100    0.79 0.93068834 0.92248361 0.11104968      458  145 5229
480 0.100    0.80 0.93164436 0.92646870 0.31164729      429  143 5258
481 0.100    0.81 0.93403442 0.92929682 0.34782522      412  138 5275
482 0.100    0.82 0.93881453 0.93366757 0.29143588      388  128 5299
483 0.100    0.83 0.94502868 0.93906672 0.20061137      359  115 5328
484 0.100    0.84 0.94837476 0.94215195 0.17033910      342  108 5345
485 0.100    0.85 0.95411090 0.94575138 0.05513731      326   96 5361
486 0.100    0.86 0.95841300 0.95037923 0.05484508      299   87 5388
487 0.100    0.87 0.96128107 0.95410721 0.07625655      276   81 5411
488 0.100    0.88 0.96510516 0.95834940 0.08100971      251   73 5436
489 0.100    0.89 0.96749522 0.96143463 0.10581920      232   68 5455
490 0.100    0.90 0.97131931 0.96490551 0.07265561      213   60 5474
491 0.100    0.91 0.97418738 0.96734799 0.04695978      200   54 5487
492 0.100    0.92 0.97753346 0.97159018 0.06626192      174   47 5513
493 0.100    0.93 0.98135755 0.97544672 0.04993685      152   39 5535
494 0.100    0.94 0.98231358 0.97827484 0.16324118      132   37 5555
495 0.100    0.95 0.98613767 0.98213138 0.12819855      110   29 5577
496 0.100    0.96 0.99091778 0.98624502 0.04171606       88   19 5599
497 0.100    0.97 0.99378585 0.99010156 0.06264913       64   13 5623
498 0.100    0.98 0.99474187 0.99305823 0.35197885       43   11 5644
499 0.100    0.99 0.99808795 0.99652912 0.22995331       23    4 5664
500 0.100    1.00 1.00000000 1.00000000 0.00000000        0    0 5687
    Dboth
1      17
2      25
3      29
4      35
5      39
6      47
7      54
8      62
9      69
10     79
11     83
12     89
13     91
14     96
15    104
16    108
17    117
18    123
19    127
20    134
21    139
22    150
23    160
24    171
25    176
26    183
27    192
28    198
29    202
30    211
31    216
32    220
33    228
34    232
35    236
36    244
37    255
38    259
39    270
40    277
41    283
42    292
43    294
44    300
45    307
46    309
47    315
48    321
49    333
50    336
51    340
52    348
53    351
54    351
55    353
56    357
57    359
58    366
59    368
60    372
61    372
62    379
63    380
64    387
65    391
66    393
67    397
68    399
69    400
70    407
71    408
72    411
73    411
74    413
75    414
76    416
77    416
78    420
79    422
80    423
81    424
82    427
83    430
84    431
85    433
86    436
87    437
88    439
89    440
90    442
91    444
92    444
93    446
94    446
95    450
96    452
97    453
98    453
99    456
100   457
101    36
102    52
103    58
104    70
105    80
106    94
107   106
108   121
109   136
110   152
111   161
112   175
113   180
114   193
115   207
116   213
117   231
118   246
119   259
120   272
121   280
122   294
123   309
124   326
125   339
126   355
127   369
128   383
129   392
130   408
131   426
132   432
133   451
134   462
135   469
136   483
137   502
138   509
139   533
140   549
141   561
142   582
143   592
144   604
145   616
146   621
147   630
148   644
149   659
150   670
151   677
152   689
153   694
154   699
155   708
156   713
157   716
158   725
159   732
160   746
161   748
162   759
163   762
164   772
165   779
166   786
167   790
168   798
169   802
170   814
171   817
172   822
173   825
174   829
175   831
176   836
177   842
178   847
179   849
180   850
181   851
182   856
183   861
184   864
185   870
186   875
187   876
188   881
189   883
190   888
191   892
192   895
193   898
194   899
195   906
196   911
197   913
198   915
199   918
200   920
201    64
202    87
203    96
204   115
205   129
206   147
207   162
208   184
209   206
210   229
211   244
212   267
213   274
214   296
215   317
216   330
217   355
218   379
219   398
220   417
221   429
222   454
223   473
224   505
225   526
226   547
227   563
228   590
229   604
230   627
231   655
232   667
233   698
234   721
235   736
236   757
237   787
238   801
239   837
240   858
241   876
242   901
243   919
244   939
245   953
246   964
247   977
248   995
249  1013
250  1028
251  1039
252  1056
253  1065
254  1075
255  1089
256  1099
257  1106
258  1117
259  1125
260  1148
261  1154
262  1167
263  1174
264  1186
265  1194
266  1202
267  1209
268  1217
269  1223
270  1241
271  1245
272  1251
273  1255
274  1261
275  1266
276  1274
277  1285
278  1292
279  1296
280  1297
281  1299
282  1306
283  1312
284  1317
285  1326
286  1334
287  1337
288  1344
289  1348
290  1354
291  1358
292  1364
293  1369
294  1371
295  1379
296  1386
297  1389
298  1391
299  1395
300  1397
301    84
302   113
303   127
304   148
305   164
306   188
307   208
308   235
309   265
310   290
311   305
312   332
313   340
314   367
315   388
316   409
317   441
318   468
319   495
320   519
321   539
322   572
323   599
324   641
325   665
326   690
327   715
328   748
329   770
330   799
331   834
332   848
333   890
334   918
335   939
336   967
337  1004
338  1022
339  1064
340  1093
341  1111
342  1138
343  1162
344  1189
345  1210
346  1227
347  1245
348  1269
349  1294
350  1311
351  1323
352  1349
353  1362
354  1375
355  1392
356  1404
357  1415
358  1431
359  1442
360  1467
361  1477
362  1491
363  1503
364  1516
365  1526
366  1536
367  1544
368  1552
369  1562
370  1581
371  1588
372  1594
373  1598
374  1606
375  1613
376  1621
377  1636
378  1644
379  1649
380  1650
381  1653
382  1660
383  1670
384  1676
385  1686
386  1694
387  1698
388  1706
389  1710
390  1717
391  1722
392  1729
393  1736
394  1738
395  1746
396  1754
397  1759
398  1761
399  1767
400  1770
401   100
402   132
403   150
404   175
405   194
406   222
407   244
408   275
409   311
410   340
411   358
412   393
413   406
414   437
415   464
416   491
417   527
418   555
419   588
420   618
421   639
422   679
423   714
424   762
425   789
426   821
427   856
428   895
429   919
430   952
431   992
432  1012
433  1059
434  1087
435  1113
436  1143
437  1181
438  1205
439  1252
440  1286
441  1310
442  1340
443  1371
444  1405
445  1429
446  1449
447  1471
448  1501
449  1529
450  1551
451  1565
452  1594
453  1609
454  1624
455  1642
456  1655
457  1666
458  1685
459  1699
460  1725
461  1736
462  1752
463  1769
464  1784
465  1798
466  1811
467  1820
468  1830
469  1843
470  1862
471  1873
472  1880
473  1885
474  1893
475  1902
476  1911
477  1930
478  1941
479  1947
480  1949
481  1954
482  1964
483  1977
484  1984
485  1996
486  2005
487  2011
488  2019
489  2024
490  2032
491  2038
492  2045
493  2053
494  2055
495  2063
496  2073
497  2079
498  2081
499  2088
500  2092
#enrichment.plotter(h_US, "USFDR", "adj.P.Val", "FDR for Closest Upstream Hi-C Contact Overlapping Gene, Human") #These two are ugly, and can't be run anyway until next chunk is complete to create their DFs. It's OK without them.
#enrichment.plotter(c_US, "USFDR", "adj.P.Val", "FDR for Closest Upstream Hi-C Contact Overlapping Gene, Chimp")
enrichment.plotter(gene.hic.filt, "max_B_FDR.H", "adj.P.Val", "FDR for Hi-C Contact Overlapping Gene w/ Strongest Effect Size, Human")
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp     chisq.p Dneither   DE DHiC
1   0.010    0.01 0.04255319 0.04482226 0.896341593     6966  450  328
2   0.010    0.02 0.05531915 0.05873261 0.823132279     6864  444  430
3   0.010    0.03 0.06595745 0.06774858 0.948388489     6799  439  495
4   0.010    0.04 0.08297872 0.07792375 0.739109091     6728  431  566
5   0.010    0.05 0.09361702 0.08861412 0.756539910     6650  426  644
6   0.010    0.06 0.10638298 0.09994848 0.688779537     6568  420  726
7   0.010    0.07 0.12127660 0.10935085 0.436282525     6502  413  792
8   0.010    0.08 0.14042553 0.12017002 0.186783684     6427  404  867
9   0.010    0.09 0.15319149 0.13227718 0.190016651     6339  398  955
10  0.010    0.10 0.16595745 0.14013395 0.110625351     6284  392 1010
11  0.010    0.11 0.17446809 0.15108192 0.163272439     6203  388 1091
12  0.010    0.12 0.19148936 0.16280268 0.094223648     6120  380 1174
13  0.010    0.13 0.20212766 0.17349304 0.103414230     6042  375 1252
14  0.010    0.14 0.21489362 0.18495621 0.096241734     5959  369 1335
15  0.010    0.15 0.22978723 0.19706337 0.075037993     5872  362 1422
16  0.010    0.16 0.24468085 0.20852653 0.053363753     5790  355 1504
17  0.010    0.17 0.26170213 0.22230809 0.039216814     5691  347 1603
18  0.010    0.18 0.27659574 0.23402885 0.028340342     5607  340 1687
19  0.010    0.19 0.28510638 0.24729521 0.056768894     5508  336 1786
20  0.010    0.20 0.31063830 0.26313756 0.018335106     5397  324 1897
21  0.010    0.21 0.31702128 0.27228233 0.028193632     5329  321 1965
22  0.010    0.22 0.33829787 0.28851108 0.016157245     5213  311 2081
23  0.010    0.23 0.35744681 0.30203503 0.008107401     5117  302 2177
24  0.010    0.24 0.37021277 0.31736218 0.012824793     5004  296 2290
25  0.010    0.25 0.37659574 0.33191654 0.038297090     4894  293 2400
26  0.010    0.26 0.39787234 0.35097888 0.031733005     4756  283 2538
27  0.010    0.27 0.41489362 0.36810922 0.033975104     4631  275 2663
28  0.010    0.28 0.42340426 0.38446677 0.081618865     4508  271 2786
29  0.010    0.29 0.42978723 0.39966512 0.184546153     4393  268 2901
30  0.010    0.30 0.45106383 0.41486347 0.110691080     4285  258 3009
31  0.010    0.31 0.46382979 0.42967543 0.134878441     4176  252 3118
32  0.010    0.32 0.47234043 0.44165379 0.182116831     4087  248 3207
33  0.010    0.33 0.48723404 0.46097372 0.258227010     3944  241 3350
34  0.010    0.34 0.49787234 0.47578568 0.346426915     3834  236 3460
35  0.010    0.35 0.50638298 0.48969603 0.484530376     3730  232 3564
36  0.010    0.36 0.51914894 0.50167439 0.462873952     3643  226 3651
37  0.010    0.37 0.54042553 0.52073673 0.404343606     3505  216 3789
38  0.010    0.38 0.55319149 0.53941267 0.568291880     3366  210 3928
39  0.010    0.39 0.57021277 0.55692942 0.582177184     3238  202 4056
40  0.010    0.40 0.58510638 0.57264297 0.606260207     3123  195 4171
41  0.010    0.41 0.60212766 0.58629572 0.502409757     3025  187 4269
42  0.010    0.42 0.62340426 0.60226687 0.358950831     2911  177 4383
43  0.010    0.43 0.62765957 0.61720762 0.665736782     2797  175 4497
44  0.010    0.44 0.64468085 0.63008758 0.530781211     2705  167 4589
45  0.010    0.45 0.66595745 0.64799073 0.428591225     2576  157 4718
46  0.010    0.46 0.67021277 0.66164348 0.722737688     2472  155 4822
47  0.010    0.47 0.68723404 0.67555384 0.612010811     2372  147 4922
48  0.010    0.48 0.69787234 0.68650180 0.619242304     2292  142 5002
49  0.010    0.49 0.71914894 0.69577537 0.278096782     2230  132 5064
50  0.010    0.50 0.73191489 0.70852653 0.271860903     2137  126 5157
51  0.010    0.51 0.75319149 0.71818650 0.091513096     2072  116 5222
52  0.010    0.52 0.77021277 0.73042246 0.050933914     1985  108 5309
53  0.010    0.53 0.77659574 0.74227202 0.088970215     1896  105 5398
54  0.010    0.54 0.78085106 0.75128800 0.140305286     1828  103 5466
55  0.010    0.55 0.78723404 0.76339516 0.230675497     1737  100 5557
56  0.010    0.56 0.80425532 0.77241113 0.100582484     1675   92 5619
57  0.010    0.57 0.80638298 0.77988150 0.169681007     1618   91 5676
58  0.010    0.58 0.82127660 0.78967027 0.093688267     1549   84 5745
59  0.010    0.59 0.82553191 0.79778465 0.137295513     1488   82 5806
60  0.010    0.60 0.83191489 0.80654302 0.168689782     1423   79 5871
61  0.010    0.61 0.83191489 0.81465739 0.351266577     1360   79 5934
62  0.010    0.62 0.84468085 0.82264297 0.219380183     1304   73 5990
63  0.010    0.63 0.84893617 0.82934055 0.270557576     1254   71 6040
64  0.010    0.64 0.85957447 0.83719732 0.196612013     1198   66 6096
65  0.010    0.65 0.86170213 0.84621329 0.371114856     1129   65 6165
66  0.010    0.66 0.86808511 0.85394127 0.407445078     1072   62 6222
67  0.010    0.67 0.87446809 0.86038125 0.400665983     1025   59 6269
68  0.010    0.68 0.88085106 0.86450283 0.317857745      996   56 6298
69  0.010    0.69 0.88510638 0.87107161 0.386641950      947   54 6347
70  0.010    0.70 0.89361702 0.87815559 0.324875631      896   50 6398
71  0.010    0.71 0.90000000 0.88330757 0.276238359      859   47 6435
72  0.010    0.72 0.90638298 0.89116435 0.309346013      801   44 6493
73  0.010    0.73 0.90638298 0.89528594 0.463598044      769   44 6525
74  0.010    0.74 0.90638298 0.90043792 0.715380192      729   44 6565
75  0.010    0.75 0.91063830 0.90443071 0.695553513      700   42 6594
76  0.010    0.76 0.91702128 0.90803709 0.539843942      675   39 6619
77  0.010    0.77 0.91914894 0.91447707 0.772910246      626   38 6668
78  0.010    0.78 0.93617021 0.92014426 0.216984862      590   30 6704
79  0.010    0.79 0.94042553 0.92387944 0.191612567      563   28 6731
80  0.010    0.80 0.94042553 0.92787223 0.320526913      532   28 6762
81  0.010    0.81 0.94468085 0.93134982 0.277869297      507   26 6787
82  0.010    0.82 0.95106383 0.93572901 0.193050135      476   23 6818
83  0.010    0.83 0.95319149 0.94062339 0.276237487      439   22 6855
84  0.010    0.84 0.95744681 0.94474498 0.254571528      409   20 6885
85  0.010    0.85 0.95957447 0.94757857 0.272594404      388   19 6906
86  0.010    0.86 0.96382979 0.95105616 0.224761047      363   17 6931
87  0.010    0.87 0.96595745 0.95492014 0.282294973      334   16 6960
88  0.010    0.88 0.96808511 0.95878413 0.354022806      305   15 6989
89  0.010    0.89 0.97021277 0.96251932 0.434974134      277   14 7017
90  0.010    0.90 0.97234043 0.96548171 0.477705507      255   13 7039
91  0.010    0.91 0.97234043 0.96805770 0.682222700      235   13 7059
92  0.010    0.92 0.97234043 0.97217929 1.000000000      203   13 7091
93  0.010    0.93 0.97659574 0.97591448 1.000000000      176   11 7118
94  0.010    0.94 0.97872340 0.97887687 1.000000000      154   10 7140
95  0.010    0.95 0.98723404 0.98183926 0.468178083      135    6 7159
96  0.010    0.96 0.99361702 0.98596084 0.210103389      106    3 7188
97  0.010    0.97 0.99574468 0.98969603 0.269553541       78    2 7216
98  0.010    0.98 0.99574468 0.99291602 0.637876460       53    2 7241
99  0.010    0.99 0.99787234 0.99639361 0.876970946       27    1 7267
100 0.010    1.00 1.00000000 1.00000000 0.000000000        0    0 7294
101 0.025    0.01 0.03900325 0.04482226 0.409099524     6529  887  312
102 0.025    0.02 0.05308776 0.05873261 0.482388519     6434  874  407
103 0.025    0.03 0.06067172 0.06774858 0.399993514     6371  867  470
104 0.025    0.04 0.07583965 0.07792375 0.852261448     6306  853  535
105 0.025    0.05 0.08667389 0.08861412 0.873451994     6233  843  608
106 0.025    0.06 0.10075840 0.09994848 0.976910867     6158  830  683
107 0.025    0.07 0.11592633 0.10935085 0.531472350     6099  816  742
108 0.025    0.08 0.13326111 0.12017002 0.211616544     6031  800  810
109 0.025    0.09 0.14517876 0.13227718 0.237694465     5948  789  893
110 0.025    0.10 0.15492958 0.14013395 0.183842024     5896  780  945
111 0.025    0.11 0.16251354 0.15108192 0.325033015     5818  773 1023
112 0.025    0.12 0.17551463 0.16280268 0.286001027     5739  761 1102
113 0.025    0.13 0.18526544 0.17349304 0.337105911     5665  752 1176
114 0.025    0.14 0.19609967 0.18495621 0.376823241     5586  742 1255
115 0.025    0.15 0.20910076 0.19706337 0.349607245     5504  730 1337
116 0.025    0.16 0.22318527 0.20852653 0.260725688     5428  717 1413
117 0.025    0.17 0.23943662 0.22230809 0.196663204     5336  702 1505
118 0.025    0.18 0.25568797 0.23402885 0.106462902     5260  687 1581
119 0.025    0.19 0.26652221 0.24729521 0.160996761     5167  677 1674
120 0.025    0.20 0.28494041 0.26313756 0.118114569     5061  660 1780
121 0.025    0.21 0.29144095 0.27228233 0.175854126     4996  654 1845
122 0.025    0.22 0.30660888 0.28851108 0.209790687     4884  640 1957
123 0.025    0.23 0.31852654 0.30203503 0.260873330     4790  629 2051
124 0.025    0.24 0.33152763 0.31736218 0.343464171     4683  617 2158
125 0.025    0.25 0.34127844 0.33191654 0.544367096     4579  608 2262
126 0.025    0.26 0.35752979 0.35097888 0.683638483     4446  593 2395
127 0.025    0.27 0.37594800 0.36810922 0.624352281     4330  576 2511
128 0.025    0.28 0.38569881 0.38446677 0.963367147     4212  567 2629
129 0.025    0.29 0.39219935 0.39966512 0.647305202     4100  561 2741
130 0.025    0.30 0.41386782 0.41486347 0.976211057     4002  541 2839
131 0.025    0.31 0.43011918 0.42967543 1.000000000     3902  526 2939
132 0.025    0.32 0.43661972 0.44165379 0.769678017     3815  520 3026
133 0.025    0.33 0.45612134 0.46097372 0.779562828     3683  502 3158
134 0.025    0.34 0.47128927 0.47578568 0.797724799     3582  488 3259
135 0.025    0.35 0.48320693 0.48969603 0.700190424     3485  477 3356
136 0.025    0.36 0.49404117 0.50167439 0.646201946     3402  467 3439
137 0.025    0.37 0.51354280 0.52073673 0.666484675     3272  449 3569
138 0.025    0.38 0.53087757 0.53941267 0.603735039     3143  433 3698
139 0.025    0.39 0.54712893 0.55692942 0.546339017     3022  418 3819
140 0.025    0.40 0.55796316 0.57264297 0.354970893     2910  408 3931
141 0.025    0.41 0.56988082 0.58629572 0.296881201     2815  397 4026
142 0.025    0.42 0.59046587 0.60226687 0.456532878     2710  378 4131
143 0.025    0.43 0.60238353 0.61720762 0.341596994     2605  367 4236
144 0.025    0.44 0.61755146 0.63008758 0.421336332     2519  353 4322
145 0.025    0.45 0.63705309 0.64799073 0.481116816     2398  335 4443
146 0.025    0.46 0.64355363 0.66164348 0.229995117     2298  329 4543
147 0.025    0.47 0.65872156 0.67555384 0.260077391     2204  315 4637
148 0.025    0.48 0.66955580 0.68650180 0.252430287     2129  305 4712
149 0.025    0.49 0.68147346 0.69577537 0.333042506     2068  294 4773
150 0.025    0.50 0.69664139 0.70852653 0.419155444     1983  280 4858
151 0.025    0.51 0.71397616 0.71818650 0.791834371     1924  264 4917
152 0.025    0.52 0.72914410 0.73042246 0.957150034     1843  250 4998
153 0.025    0.53 0.73781148 0.74227202 0.771826574     1759  242 5082
154 0.025    0.54 0.74431203 0.75128800 0.629976481     1695  236 5146
155 0.025    0.55 0.75406284 0.76339516 0.503210422     1610  227 5231
156 0.025    0.56 0.76489707 0.77241113 0.590422712     1550  217 5291
157 0.025    0.57 0.76923077 0.77988150 0.429715417     1496  213 5345
158 0.025    0.58 0.78006501 0.78967027 0.471650832     1430  203 5411
159 0.025    0.59 0.78656555 0.79778465 0.389570171     1373  197 5468
160 0.025    0.60 0.80173348 0.80654302 0.726570337     1319  183 5522
161 0.025    0.61 0.80390033 0.81465739 0.394842672     1258  181 5583
162 0.025    0.62 0.81690141 0.82264297 0.659502593     1208  169 5633
163 0.025    0.63 0.82123510 0.82934055 0.515232924     1160  165 5681
164 0.025    0.64 0.82990249 0.83719732 0.553830766     1107  157 5734
165 0.025    0.65 0.83531961 0.84621329 0.353009029     1042  152 5799
166 0.025    0.66 0.84398700 0.85394127 0.388352838      990  144 5851
167 0.025    0.67 0.84832069 0.86038125 0.282079055      944  140 5897
168 0.025    0.68 0.85482124 0.86450283 0.387410213      918  134 5923
169 0.025    0.69 0.86457205 0.87107161 0.565018524      876  125 5965
170 0.025    0.70 0.87757313 0.87815559 0.996783158      833  113 6008
171 0.025    0.71 0.88190683 0.88330757 0.930989466      797  109 6044
172 0.025    0.72 0.89165764 0.89116435 1.000000000      745  100 6096
173 0.025    0.73 0.89599133 0.89528594 0.986195216      717   96 6124
174 0.025    0.74 0.90032503 0.90043792 1.000000000      681   92 6160
175 0.025    0.75 0.90465872 0.90443071 1.000000000      654   88 6187
176 0.025    0.76 0.91007584 0.90803709 0.866842335      631   83 6210
177 0.025    0.77 0.91440953 0.91447707 1.000000000      585   79 6256
178 0.025    0.78 0.92849404 0.92014426 0.351191485      554   66 6287
179 0.025    0.79 0.93066089 0.92387944 0.446336191      527   64 6314
180 0.025    0.80 0.93066089 0.92787223 0.778623659      496   64 6345
181 0.025    0.81 0.93391116 0.93134982 0.796013081      472   61 6369
182 0.025    0.82 0.93716143 0.93572901 0.906420740      441   58 6400
183 0.025    0.83 0.94149512 0.94062339 0.963950075      407   54 6434
184 0.025    0.84 0.94691224 0.94474498 0.817880036      380   49 6461
185 0.025    0.85 0.95232936 0.94757857 0.541043219      363   44 6478
186 0.025    0.86 0.95774648 0.95105616 0.356331723      341   39 6500
187 0.025    0.87 0.95882990 0.95492014 0.599307648      312   38 6529
188 0.025    0.88 0.96316360 0.95878413 0.532076641      286   34 6555
189 0.025    0.89 0.96749729 0.96251932 0.449679957      261   30 6580
190 0.025    0.90 0.96966414 0.96548171 0.518624628      240   28 6601
191 0.025    0.91 0.97183099 0.96805770 0.551983594      222   26 6619
192 0.025    0.92 0.97399783 0.97217929 0.801596533      192   24 6649
193 0.025    0.93 0.97616468 0.97591448 1.000000000      165   22 6676
194 0.025    0.94 0.97833153 0.97887687 0.999348421      144   20 6697
195 0.025    0.95 0.98483207 0.98183926 0.552446875      127   14 6714
196 0.025    0.96 0.99241603 0.98596084 0.103785697      102    7 6739
197 0.025    0.97 0.99458288 0.98969603 0.163733245       75    5 6766
198 0.025    0.98 0.99674973 0.99291602 0.203934252       52    3 6789
199 0.025    0.99 0.99783315 0.99639361 0.627847272       26    2 6815
200 0.025    1.00 1.00000000 1.00000000 0.000000000        0    0 6841
201 0.050    0.01 0.04425410 0.04482226 0.966327190     6077 1339  286
202 0.050    0.02 0.05781585 0.05873261 0.921572702     5988 1320  375
203 0.050    0.03 0.06495360 0.06774858 0.688338729     5928 1310  435
204 0.050    0.04 0.07851535 0.07792375 0.971120818     5868 1291  495
205 0.050    0.05 0.08993576 0.08861412 0.888374972     5801 1275  562
206 0.050    0.06 0.10206995 0.09994848 0.807812574     5730 1258  633
207 0.050    0.07 0.11277659 0.10935085 0.684319152     5672 1243  691
208 0.050    0.08 0.12705211 0.12017002 0.406701595     5608 1223  755
209 0.050    0.09 0.13990007 0.13227718 0.375221760     5532 1205  831
210 0.050    0.10 0.15060671 0.14013395 0.228246173     5486 1190  877
211 0.050    0.11 0.15845824 0.15108192 0.417715951     5412 1179  951
212 0.050    0.12 0.16987866 0.16280268 0.451760629     5337 1163 1026
213 0.050    0.13 0.17773019 0.17349304 0.671806719     5265 1152 1098
214 0.050    0.14 0.19057816 0.18495621 0.575020636     5194 1134 1169
215 0.050    0.15 0.20342612 0.19706337 0.532459233     5118 1116 1245
216 0.050    0.16 0.21841542 0.20852653 0.331997299     5050 1095 1313
217 0.050    0.17 0.23483226 0.22230809 0.226324013     4966 1072 1397
218 0.050    0.18 0.25053533 0.23402885 0.114778942     4897 1050 1466
219 0.050    0.19 0.26195575 0.24729521 0.170453614     4810 1034 1553
220 0.050    0.20 0.27980014 0.26313756 0.125760321     4712 1009 1651
221 0.050    0.21 0.28551035 0.27228233 0.231884339     4649 1001 1714
222 0.050    0.22 0.30549607 0.28851108 0.129158364     4551  973 1812
223 0.050    0.23 0.31977159 0.30203503 0.117572273     4466  953 1897
224 0.050    0.24 0.33618844 0.31736218 0.100874705     4370  930 1993
225 0.050    0.25 0.34903640 0.33191654 0.141071775     4275  912 2088
226 0.050    0.26 0.36259814 0.35097888 0.329241204     4146  893 2217
227 0.050    0.27 0.37758744 0.36810922 0.434243345     4034  872 2329
228 0.050    0.28 0.39614561 0.38446677 0.335913883     3933  846 2430
229 0.050    0.29 0.40613847 0.39966512 0.605657996     3829  832 2534
230 0.050    0.30 0.42326909 0.41486347 0.499405726     3735  808 2628
231 0.050    0.31 0.44182727 0.42967543 0.324557714     3646  782 2717
232 0.050    0.32 0.44825125 0.44165379 0.603347795     3562  773 2801
233 0.050    0.33 0.47037830 0.46097372 0.452979889     3443  742 2920
234 0.050    0.34 0.48608137 0.47578568 0.410610278     3350  720 3013
235 0.050    0.35 0.49607423 0.48969603 0.618472018     3256  706 3107
236 0.050    0.36 0.50606709 0.50167439 0.738583879     3177  692 3186
237 0.050    0.37 0.52391149 0.52073673 0.815594794     3054  667 3309
238 0.050    0.38 0.54104211 0.53941267 0.915933371     2933  643 3430
239 0.050    0.39 0.56031406 0.55692942 0.801034511     2824  616 3539
240 0.050    0.40 0.57316203 0.57264297 0.989185781     2720  598 3643
241 0.050    0.41 0.58529622 0.58629572 0.956976033     2631  581 3732
242 0.050    0.42 0.60599572 0.60226687 0.775755918     2536  552 3827
243 0.050    0.43 0.61955746 0.61720762 0.865385126     2439  533 3924
244 0.050    0.44 0.63740186 0.63008758 0.551284609     2364  508 3999
245 0.050    0.45 0.65453248 0.64799073 0.592355307     2249  484 4114
246 0.050    0.46 0.66381156 0.66164348 0.874244741     2156  471 4207
247 0.050    0.47 0.67523198 0.67555384 1.000000000     2064  455 4299
248 0.050    0.48 0.68593862 0.68650180 0.985330771     1994  440 4369
249 0.050    0.49 0.69450393 0.69577537 0.934496785     1934  428 4429
250 0.050    0.50 0.70735189 0.70852653 0.940691747     1853  410 4510
251 0.050    0.51 0.72376874 0.71818650 0.631066064     1801  387 4562
252 0.050    0.52 0.73947181 0.73042246 0.417983692     1728  365 4635
253 0.050    0.53 0.74803712 0.74227202 0.609185687     1648  353 4715
254 0.050    0.54 0.75588865 0.75128800 0.684807998     1589  342 4774
255 0.050    0.55 0.76659529 0.76339516 0.782084178     1510  327 4853
256 0.050    0.56 0.77658815 0.77241113 0.706387409     1454  313 4909
257 0.050    0.57 0.78229836 0.77988150 0.837131026     1404  305 4959
258 0.050    0.58 0.79086367 0.78967027 0.932368868     1340  293 5023
259 0.050    0.59 0.79800143 0.79778465 1.000000000     1287  283 5076
260 0.050    0.60 0.81227695 0.80654302 0.573558797     1239  263 5124
261 0.050    0.61 0.81655960 0.81465739 0.869394767     1182  257 5181
262 0.050    0.62 0.82655246 0.82264297 0.700573912     1134  243 5229
263 0.050    0.63 0.83297645 0.82934055 0.718574470     1091  234 5272
264 0.050    0.64 0.83940043 0.83719732 0.836196197     1039  225 5324
265 0.050    0.65 0.84511064 0.84621329 0.931884283      977  217 5386
266 0.050    0.66 0.85153462 0.85394127 0.810353751      926  208 5437
267 0.050    0.67 0.85581727 0.86038125 0.615756024      882  202 5481
268 0.050    0.68 0.86009993 0.86450283 0.624999984      856  196 5507
269 0.050    0.69 0.86866524 0.87107161 0.800378927      817  184 5546
270 0.050    0.70 0.88079943 0.87815559 0.772529750      779  167 5584
271 0.050    0.71 0.88436831 0.88330757 0.927776670      744  162 5619
272 0.050    0.72 0.89436117 0.89116435 0.706152102      697  148 5666
273 0.050    0.73 0.89793005 0.89528594 0.757430693      670  143 5693
274 0.050    0.74 0.90364026 0.90043792 0.694375973      638  135 5725
275 0.050    0.75 0.90935046 0.90443071 0.521077483      615  127 5748
276 0.050    0.76 0.91577445 0.90803709 0.290976530      596  118 5767
277 0.050    0.77 0.92005710 0.91447707 0.439990622      552  112 5811
278 0.050    0.78 0.93076374 0.92014426 0.117504554      523   97 5840
279 0.050    0.79 0.93290507 0.92387944 0.176523384      497   94 5866
280 0.050    0.80 0.93290507 0.92787223 0.454871776      466   94 5897
281 0.050    0.81 0.93647395 0.93134982 0.435680516      444   89 5919
282 0.050    0.82 0.93932905 0.93572901 0.584526705      414   85 5949
283 0.050    0.83 0.94218415 0.94062339 0.833184745      380   81 5983
284 0.050    0.84 0.94718059 0.94474498 0.706790747      355   74 6008
285 0.050    0.85 0.95074946 0.94757857 0.601650421      338   69 6025
286 0.050    0.86 0.95574590 0.95105616 0.406350283      318   62 6045
287 0.050    0.87 0.95931478 0.95492014 0.421034795      293   57 6070
288 0.050    0.88 0.96359743 0.95878413 0.353988942      269   51 6094
289 0.050    0.89 0.96859386 0.96251932 0.213267798      247   44 6116
290 0.050    0.90 0.97144897 0.96548171 0.203853699      228   40 6135
291 0.050    0.91 0.97359029 0.96805770 0.223629915      211   37 6152
292 0.050    0.92 0.97715917 0.97217929 0.245136702      184   32 6179
293 0.050    0.93 0.97930050 0.97591448 0.413989201      158   29 6205
294 0.050    0.94 0.98072805 0.97887687 0.667443456      137   27 6226
295 0.050    0.95 0.98501071 0.98183926 0.383495345      120   21 6243
296 0.050    0.96 0.99072091 0.98596084 0.121771567       96   13 6267
297 0.050    0.97 0.99428979 0.98969603 0.082794877       72    8 6291
298 0.050    0.98 0.99643112 0.99291602 0.119480340       50    5 6313
299 0.050    0.99 0.99785867 0.99639361 0.444664563       25    3 6338
300 0.050    1.00 1.00000000 1.00000000 0.000000000        0    0 6363
301 0.075    0.01 0.04643262 0.04482226 0.759082704     5732 1684  266
302 0.075    0.02 0.05832390 0.05873261 0.979625428     5645 1663  353
303 0.075    0.03 0.06681767 0.06774858 0.901916804     5590 1648  408
304 0.075    0.04 0.07927520 0.07792375 0.848874834     5533 1626  465
305 0.075    0.05 0.09173273 0.08861412 0.633329594     5472 1604  526
306 0.075    0.06 0.10362401 0.09994848 0.588659280     5405 1583  593
307 0.075    0.07 0.11494904 0.10935085 0.415479190     5352 1563  646
308 0.075    0.08 0.12910532 0.12017002 0.203294077     5293 1538  705
309 0.075    0.09 0.14326161 0.13227718 0.130988656     5224 1513  774
310 0.075    0.10 0.15288788 0.14013395 0.085854981     5180 1496  818
311 0.075    0.11 0.16081540 0.15108192 0.207069320     5109 1482  889
312 0.075    0.12 0.17044168 0.16280268 0.340777499     5035 1465  963
313 0.075    0.13 0.17780294 0.17349304 0.611154546     4965 1452 1033
314 0.075    0.14 0.18969422 0.18495621 0.583287639     4897 1431 1101
315 0.075    0.15 0.19988675 0.19706337 0.760115330     4821 1413 1177
316 0.075    0.16 0.21460929 0.20852653 0.494889534     4758 1387 1240
317 0.075    0.17 0.23159683 0.22230809 0.300416862     4681 1357 1317
318 0.075    0.18 0.24631937 0.23402885 0.175116189     4616 1331 1382
319 0.075    0.19 0.25934315 0.24729521 0.192313271     4536 1308 1462
320 0.075    0.20 0.27633069 0.26313756 0.160983965     4443 1278 1555
321 0.075    0.21 0.28425821 0.27228233 0.209146431     4386 1264 1612
322 0.075    0.22 0.30407701 0.28851108 0.106794262     4295 1229 1703
323 0.075    0.23 0.31879955 0.30203503 0.086114388     4216 1203 1782
324 0.075    0.24 0.33578709 0.31736218 0.062384350     4127 1173 1871
325 0.075    0.25 0.34824462 0.33191654 0.103295114     4036 1151 1962
326 0.075    0.26 0.36353341 0.35097888 0.218957831     3915 1124 2083
327 0.075    0.27 0.38052095 0.36810922 0.229222144     3812 1094 2186
328 0.075    0.28 0.39920725 0.38446677 0.155341091     3718 1061 2280
329 0.075    0.29 0.41223103 0.39966512 0.230562734     3623 1038 2375
330 0.075    0.30 0.42808607 0.41486347 0.209241180     3533 1010 2465
331 0.075    0.31 0.44507361 0.42967543 0.144326426     3448  980 2550
332 0.075    0.32 0.45243488 0.44165379 0.312132046     3368  967 2630
333 0.075    0.33 0.47451869 0.46097372 0.203364419     3257  928 2741
334 0.075    0.34 0.49150623 0.47578568 0.139430368     3172  898 2826
335 0.075    0.35 0.50226501 0.48969603 0.239968357     3083  879 2915
336 0.075    0.36 0.51302378 0.50167439 0.289963702     3009  860 2989
337 0.075    0.37 0.53114383 0.52073673 0.332583360     2893  828 3105
338 0.075    0.38 0.54869762 0.53941267 0.387877476     2779  797 3219
339 0.075    0.39 0.56625142 0.55692942 0.384307703     2674  766 3324
340 0.075    0.40 0.57927520 0.57264297 0.539456670     2575  743 3423
341 0.075    0.41 0.59003398 0.58629572 0.737304561     2488  724 3510
342 0.075    0.42 0.60872027 0.60226687 0.546664212     2397  691 3601
343 0.075    0.43 0.62287656 0.61720762 0.596270570     2306  666 3692
344 0.075    0.44 0.64269536 0.63008758 0.222252304     2241  631 3757
345 0.075    0.45 0.66138165 0.64799073 0.189449349     2135  598 3863
346 0.075    0.46 0.67157418 0.66164348 0.329617127     2047  580 3951
347 0.075    0.47 0.68403171 0.67555384 0.402653638     1961  558 4037
348 0.075    0.48 0.69762174 0.68650180 0.264054799     1900  534 4098
349 0.075    0.49 0.70724802 0.69577537 0.244900266     1845  517 4153
350 0.075    0.50 0.71970555 0.70852653 0.251647286     1768  495 4230
351 0.075    0.51 0.73499434 0.71818650 0.079057550     1720  468 4278
352 0.075    0.52 0.74971687 0.73042246 0.040519576     1651  442 4347
353 0.075    0.53 0.75877690 0.74227202 0.076187157     1575  426 4423
354 0.075    0.54 0.76727067 0.75128800 0.082478568     1520  411 4478
355 0.075    0.55 0.77802945 0.76339516 0.106421118     1445  392 4553
356 0.075    0.56 0.78652322 0.77241113 0.114801366     1390  377 4608
357 0.075    0.57 0.79161948 0.77988150 0.186218616     1341  368 4657
358 0.075    0.58 0.80181200 0.78967027 0.164159232     1283  350 4715
359 0.075    0.59 0.80804077 0.79778465 0.235162975     1231  339 4767
360 0.075    0.60 0.82106455 0.80654302 0.084813165     1186  316 4812
361 0.075    0.61 0.82616082 0.81465739 0.167405685     1132  307 4866
362 0.075    0.62 0.83465459 0.82264297 0.142084802     1085  292 4913
363 0.075    0.63 0.84314836 0.82934055 0.085647115     1048  277 4950
364 0.075    0.64 0.84994337 0.83719732 0.106521981      999  265 4999
365 0.075    0.65 0.85617214 0.84621329 0.199707064      940  254 5058
366 0.075    0.66 0.86183465 0.85394127 0.302876995      890  244 5108
367 0.075    0.67 0.86636467 0.86038125 0.431663679      848  236 5150
368 0.075    0.68 0.87032843 0.86450283 0.438774080      823  229 5175
369 0.075    0.69 0.87768969 0.87107161 0.366096011      785  216 5213
370 0.075    0.70 0.88901472 0.87815559 0.122140180      750  196 5248
371 0.075    0.71 0.89241223 0.88330757 0.188941703      716  190 5282
372 0.075    0.72 0.90033975 0.89116435 0.172202954      669  176 5329
373 0.075    0.73 0.90317101 0.89528594 0.235200002      642  171 5356
374 0.075    0.74 0.90883352 0.90043792 0.195171337      612  161 5386
375 0.075    0.75 0.91392978 0.90443071 0.133939295      590  152 5408
376 0.075    0.76 0.91902605 0.90803709 0.076507529      571  143 5427
377 0.075    0.77 0.92412231 0.91447707 0.109467041      530  134 5468
378 0.075    0.78 0.93318233 0.92014426 0.024465346      502  118 5496
379 0.075    0.79 0.93544734 0.92387944 0.041895903      477  114 5521
380 0.075    0.80 0.93544734 0.92787223 0.177762971      446  114 5552
381 0.075    0.81 0.93884485 0.93134982 0.172673292      425  108 5573
382 0.075    0.82 0.94167610 0.93572901 0.269478002      396  103 5602
383 0.075    0.83 0.94620612 0.94062339 0.283645102      366   95 5632
384 0.075    0.84 0.95073613 0.94474498 0.232291726      342   87 5656
385 0.075    0.85 0.95356738 0.94757857 0.220952636      325   82 5673
386 0.075    0.86 0.95753114 0.95105616 0.170014377      305   75 5693
387 0.075    0.87 0.96149490 0.95492014 0.147099926      282   68 5716
388 0.075    0.88 0.96489241 0.95878413 0.161202921      258   62 5740
389 0.075    0.89 0.96885617 0.96251932 0.127540049      236   55 5762
390 0.075    0.90 0.97168743 0.96548171 0.120868891      218   50 5780
391 0.075    0.91 0.97395243 0.96805770 0.127067718      202   46 5796
392 0.075    0.92 0.97734994 0.97217929 0.155342609      176   40 5822
393 0.075    0.93 0.97961495 0.97591448 0.286553750      151   36 5847
394 0.075    0.94 0.98074745 0.97887687 0.597617318      130   34 5868
395 0.075    0.95 0.98471121 0.98183926 0.353958287      114   27 5884
396 0.075    0.96 0.98980747 0.98596084 0.147576736       91   18 5907
397 0.075    0.97 0.99377123 0.98969603 0.072591625       69   11 5929
398 0.075    0.98 0.99546999 0.99291602 0.195467480       47    8 5951
399 0.075    0.99 0.99773499 0.99639361 0.398634760       24    4 5974
400 0.075    1.00 1.00000000 1.00000000 0.000000000        0    0 5998
401 0.100    0.01 0.04654511 0.04482226 0.702079771     5429 1987  251
402 0.100    0.02 0.05854127 0.05873261 1.000000000     5346 1962  334
403 0.100    0.03 0.06765835 0.06774858 1.000000000     5295 1943  385
404 0.100    0.04 0.08013436 0.07792375 0.694771422     5242 1917  438
405 0.100    0.05 0.09261036 0.08861412 0.480518339     5185 1891  495
406 0.100    0.06 0.10508637 0.09994848 0.383432678     5123 1865  557
407 0.100    0.07 0.11516315 0.10935085 0.340589585     5071 1844  609
408 0.100    0.08 0.12859885 0.12017002 0.178901527     5015 1816  665
409 0.100    0.09 0.14251440 0.13227718 0.115267785     4950 1787  730
410 0.100    0.10 0.15211132 0.14013395 0.071122232     4909 1767  771
411 0.100    0.11 0.15978887 0.15108192 0.207001123     4840 1751  840
412 0.100    0.12 0.17034549 0.16280268 0.291075486     4771 1729  909
413 0.100    0.13 0.17898273 0.17349304 0.459340643     4706 1711  974
414 0.100    0.14 0.18953935 0.18495621 0.550480190     4639 1689 1041
415 0.100    0.15 0.20009597 0.19706337 0.707876643     4567 1667 1113
416 0.100    0.16 0.21353167 0.20852653 0.531289716     4506 1639 1174
417 0.100    0.17 0.23032630 0.22230809 0.318068453     4434 1604 1246
418 0.100    0.18 0.24328215 0.23402885 0.255862777     4370 1577 1310
419 0.100    0.19 0.25575816 0.24729521 0.309033178     4293 1551 1387
420 0.100    0.20 0.27255278 0.26313756 0.266084868     4205 1516 1475
421 0.100    0.21 0.28023033 0.27228233 0.355375331     4150 1500 1530
422 0.100    0.22 0.29942418 0.28851108 0.208637450     4064 1460 1616
423 0.100    0.23 0.31525912 0.30203503 0.131213010     3992 1427 1688
424 0.100    0.24 0.33061420 0.31736218 0.135678322     3905 1395 1775
425 0.100    0.25 0.34309021 0.33191654 0.215255190     3818 1369 1862
426 0.100    0.26 0.35892514 0.35097888 0.388809117     3703 1336 1977
427 0.100    0.27 0.37763916 0.36810922 0.303915120     3609 1297 2071
428 0.100    0.28 0.39491363 0.38446677 0.262780129     3518 1261 2162
429 0.100    0.29 0.40834933 0.39966512 0.357520132     3428 1233 2252
430 0.100    0.30 0.42418426 0.41486347 0.325262132     3343 1200 2337
431 0.100    0.31 0.44193858 0.42967543 0.194870261     3265 1163 2415
432 0.100    0.32 0.45105566 0.44165379 0.324761680     3191 1144 2489
433 0.100    0.33 0.47120921 0.46097372 0.284510666     3083 1102 2597
434 0.100    0.34 0.48752399 0.47578568 0.219132771     3002 1068 2678
435 0.100    0.35 0.49904031 0.48969603 0.331025595     2918 1044 2762
436 0.100    0.36 0.50959693 0.50167439 0.412167797     2847 1022 2833
437 0.100    0.37 0.52639155 0.52073673 0.562919245     2734  987 2946
438 0.100    0.38 0.54318618 0.53941267 0.705156056     2624  952 3056
439 0.100    0.39 0.56142035 0.55692942 0.647855346     2526  914 3154
440 0.100    0.40 0.57485605 0.57264297 0.831418090     2432  886 3248
441 0.100    0.41 0.58685221 0.58629572 0.972633119     2351  861 3329
442 0.100    0.42 0.60508637 0.60226687 0.778477457     2265  823 3415
443 0.100    0.43 0.62092131 0.61720762 0.702881101     2182  790 3498
444 0.100    0.44 0.64011516 0.63008758 0.279231513     2122  750 3558
445 0.100    0.45 0.65786948 0.64799073 0.281408567     2020  713 3660
446 0.100    0.46 0.66794626 0.66164348 0.494035859     1935  692 3745
447 0.100    0.47 0.68138196 0.67555384 0.524078627     1855  664 3825
448 0.100    0.48 0.69433781 0.68650180 0.382164833     1797  637 3883
449 0.100    0.49 0.70441459 0.69577537 0.329867909     1746  616 3934
450 0.100    0.50 0.71737044 0.70852653 0.312252197     1674  589 4006
451 0.100    0.51 0.73128599 0.71818650 0.127106462     1628  560 4052
452 0.100    0.52 0.74520154 0.73042246 0.080334368     1562  531 4118
453 0.100    0.53 0.75431862 0.74227202 0.149661019     1489  512 4191
454 0.100    0.54 0.76295585 0.75128800 0.158238288     1437  494 4243
455 0.100    0.55 0.77303263 0.76339516 0.237931555     1364  473 4316
456 0.100    0.56 0.78119002 0.77241113 0.277043993     1311  456 4369
457 0.100    0.57 0.78598848 0.77988150 0.449781403     1263  446 4417
458 0.100    0.58 0.79606526 0.78967027 0.420198248     1208  425 4472
459 0.100    0.59 0.80230326 0.79778465 0.569652697     1158  412 4522
460 0.100    0.60 0.81477927 0.80654302 0.279944690     1116  386 4564
461 0.100    0.61 0.82053743 0.81465739 0.438520676     1065  374 4615
462 0.100    0.62 0.82965451 0.82264297 0.344049727     1022  355 4658
463 0.100    0.63 0.83877159 0.82934055 0.192257282      989  336 4691
464 0.100    0.64 0.84548944 0.83719732 0.244386764      942  322 4738
465 0.100    0.65 0.85316699 0.84621329 0.320559060      888  306 4792
466 0.100    0.66 0.85940499 0.85394127 0.429847361      841  293 4839
467 0.100    0.67 0.86324376 0.86038125 0.686315674      799  285 4881
468 0.100    0.68 0.86804223 0.86450283 0.606879359      777  275 4903
469 0.100    0.69 0.87523992 0.87107161 0.531545376      741  260 4939
470 0.100    0.70 0.88483685 0.87815559 0.293255968      706  240 4974
471 0.100    0.71 0.89011516 0.88330757 0.274912020      677  229 5003
472 0.100    0.72 0.89731286 0.89116435 0.311252627      631  214 5049
473 0.100    0.73 0.90019194 0.89528594 0.416007974      605  208 5075
474 0.100    0.74 0.90547025 0.90043792 0.392953026      576  197 5104
475 0.100    0.75 0.91074856 0.90443071 0.269860743      556  186 5124
476 0.100    0.76 0.91554702 0.90803709 0.179353930      538  176 5142
477 0.100    0.77 0.92130518 0.91447707 0.208627561      500  164 5180
478 0.100    0.78 0.92994242 0.92014426 0.059839129      474  146 5206
479 0.100    0.79 0.93234165 0.92387944 0.097960607      450  141 5230
480 0.100    0.80 0.93282150 0.92787223 0.331255218      420  140 5260
481 0.100    0.81 0.93714012 0.93134982 0.241376171      402  131 5278
482 0.100    0.82 0.94049904 0.93572901 0.324170028      375  124 5305
483 0.100    0.83 0.94481766 0.94062339 0.371829668      346  115 5334
484 0.100    0.84 0.95009597 0.94474498 0.232497635      325  104 5355
485 0.100    0.85 0.95393474 0.94757857 0.143010207      311   96 5369
486 0.100    0.86 0.95777351 0.95105616 0.109069382      292   88 5388
487 0.100    0.87 0.96161228 0.95492014 0.096957890      270   80 5410
488 0.100    0.88 0.96497121 0.95878413 0.110323844      247   73 5433
489 0.100    0.89 0.96880998 0.96251932 0.089080574      226   65 5454
490 0.100    0.90 0.97168906 0.96548171 0.081046156      209   59 5471
491 0.100    0.91 0.97408829 0.96805770 0.078820935      194   54 5486
492 0.100    0.92 0.97696737 0.97217929 0.139935350      168   48 5512
493 0.100    0.93 0.97936660 0.97591448 0.263462954      144   43 5536
494 0.100    0.94 0.98032630 0.97887687 0.653479756      123   41 5557
495 0.100    0.95 0.98368522 0.98183926 0.520919610      107   34 5573
496 0.100    0.96 0.98992322 0.98596084 0.091281221       88   21 5592
497 0.100    0.97 0.99424184 0.98969603 0.022860247       68   12 5612
498 0.100    0.98 0.99568138 0.99291602 0.108019375       46    9 5634
499 0.100    0.99 0.99808061 0.99639361 0.197599131       24    4 5656
500 0.100    1.00 1.00000000 1.00000000 0.000000000        0    0 5680
    Dboth
1      20
2      26
3      31
4      39
5      44
6      50
7      57
8      66
9      72
10     78
11     82
12     90
13     95
14    101
15    108
16    115
17    123
18    130
19    134
20    146
21    149
22    159
23    168
24    174
25    177
26    187
27    195
28    199
29    202
30    212
31    218
32    222
33    229
34    234
35    238
36    244
37    254
38    260
39    268
40    275
41    283
42    293
43    295
44    303
45    313
46    315
47    323
48    328
49    338
50    344
51    354
52    362
53    365
54    367
55    370
56    378
57    379
58    386
59    388
60    391
61    391
62    397
63    399
64    404
65    405
66    408
67    411
68    414
69    416
70    420
71    423
72    426
73    426
74    426
75    428
76    431
77    432
78    440
79    442
80    442
81    444
82    447
83    448
84    450
85    451
86    453
87    454
88    455
89    456
90    457
91    457
92    457
93    459
94    460
95    464
96    467
97    468
98    468
99    469
100   470
101    36
102    49
103    56
104    70
105    80
106    93
107   107
108   123
109   134
110   143
111   150
112   162
113   171
114   181
115   193
116   206
117   221
118   236
119   246
120   263
121   269
122   283
123   294
124   306
125   315
126   330
127   347
128   356
129   362
130   382
131   397
132   403
133   421
134   435
135   446
136   456
137   474
138   490
139   505
140   515
141   526
142   545
143   556
144   570
145   588
146   594
147   608
148   618
149   629
150   643
151   659
152   673
153   681
154   687
155   696
156   706
157   710
158   720
159   726
160   740
161   742
162   754
163   758
164   766
165   771
166   779
167   783
168   789
169   798
170   810
171   814
172   823
173   827
174   831
175   835
176   840
177   844
178   857
179   859
180   859
181   862
182   865
183   869
184   874
185   879
186   884
187   885
188   889
189   893
190   895
191   897
192   899
193   901
194   903
195   909
196   916
197   918
198   920
199   921
200   923
201    62
202    81
203    91
204   110
205   126
206   143
207   158
208   178
209   196
210   211
211   222
212   238
213   249
214   267
215   285
216   306
217   329
218   351
219   367
220   392
221   400
222   428
223   448
224   471
225   489
226   508
227   529
228   555
229   569
230   593
231   619
232   628
233   659
234   681
235   695
236   709
237   734
238   758
239   785
240   803
241   820
242   849
243   868
244   893
245   917
246   930
247   946
248   961
249   973
250   991
251  1014
252  1036
253  1048
254  1059
255  1074
256  1088
257  1096
258  1108
259  1118
260  1138
261  1144
262  1158
263  1167
264  1176
265  1184
266  1193
267  1199
268  1205
269  1217
270  1234
271  1239
272  1253
273  1258
274  1266
275  1274
276  1283
277  1289
278  1304
279  1307
280  1307
281  1312
282  1316
283  1320
284  1327
285  1332
286  1339
287  1344
288  1350
289  1357
290  1361
291  1364
292  1369
293  1372
294  1374
295  1380
296  1388
297  1393
298  1396
299  1398
300  1401
301    82
302   103
303   118
304   140
305   162
306   183
307   203
308   228
309   253
310   270
311   284
312   301
313   314
314   335
315   353
316   379
317   409
318   435
319   458
320   488
321   502
322   537
323   563
324   593
325   615
326   642
327   672
328   705
329   728
330   756
331   786
332   799
333   838
334   868
335   887
336   906
337   938
338   969
339  1000
340  1023
341  1042
342  1075
343  1100
344  1135
345  1168
346  1186
347  1208
348  1232
349  1249
350  1271
351  1298
352  1324
353  1340
354  1355
355  1374
356  1389
357  1398
358  1416
359  1427
360  1450
361  1459
362  1474
363  1489
364  1501
365  1512
366  1522
367  1530
368  1537
369  1550
370  1570
371  1576
372  1590
373  1595
374  1605
375  1614
376  1623
377  1632
378  1648
379  1652
380  1652
381  1658
382  1663
383  1671
384  1679
385  1684
386  1691
387  1698
388  1704
389  1711
390  1716
391  1720
392  1726
393  1730
394  1732
395  1739
396  1748
397  1755
398  1758
399  1762
400  1766
401    97
402   122
403   141
404   167
405   193
406   219
407   240
408   268
409   297
410   317
411   333
412   355
413   373
414   395
415   417
416   445
417   480
418   507
419   533
420   568
421   584
422   624
423   657
424   689
425   715
426   748
427   787
428   823
429   851
430   884
431   921
432   940
433   982
434  1016
435  1040
436  1062
437  1097
438  1132
439  1170
440  1198
441  1223
442  1261
443  1294
444  1334
445  1371
446  1392
447  1420
448  1447
449  1468
450  1495
451  1524
452  1553
453  1572
454  1590
455  1611
456  1628
457  1638
458  1659
459  1672
460  1698
461  1710
462  1729
463  1748
464  1762
465  1778
466  1791
467  1799
468  1809
469  1824
470  1844
471  1855
472  1870
473  1876
474  1887
475  1898
476  1908
477  1920
478  1938
479  1943
480  1944
481  1953
482  1960
483  1969
484  1980
485  1988
486  1996
487  2004
488  2011
489  2019
490  2025
491  2030
492  2036
493  2041
494  2043
495  2050
496  2063
497  2072
498  2075
499  2080
500  2084
enrichment.plotter(gene.hic.filt, "max_B_FDR.C", "adj.P.Val", "FDR for Hi-C Contact Overlapping Gene w/ Strongest Effect Size, Chimp")
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp    chisq.p Dneither   DE DHiC
1   0.010    0.01 0.03719912 0.04422162 0.52516767     6995  440  327
2   0.010    0.02 0.05470460 0.05913356 0.75539549     6887  432  435
3   0.010    0.03 0.06345733 0.06710374 0.82215353     6829  428  493
4   0.010    0.04 0.07439825 0.07828770 0.81863830     6747  423  575
5   0.010    0.05 0.08533917 0.08792904 0.90734845     6677  418  645
6   0.010    0.06 0.10065646 0.09949865 0.99625785     6594  411  728
7   0.010    0.07 0.11159737 0.10824013 0.87247993     6531  406  791
8   0.010    0.08 0.12910284 0.11813858 0.50043561     6462  398  860
9   0.010    0.09 0.14004376 0.13022239 0.56773142     6373  393  949
10  0.010    0.10 0.15754923 0.13909243 0.26890554     6312  385 1010
11  0.010    0.11 0.16630197 0.14899087 0.31560692     6239  381 1083
12  0.010    0.12 0.18161926 0.16068903 0.23398121     6155  374 1167
13  0.010    0.13 0.18818381 0.17058748 0.33369699     6081  371 1241
14  0.010    0.14 0.19912473 0.18151433 0.34507532     6001  366 1321
15  0.010    0.15 0.21225383 0.19449801 0.35364437     5906  360 1416
16  0.010    0.16 0.22319475 0.20439645 0.33335477     5834  355 1488
17  0.010    0.17 0.24070022 0.21943695 0.28290000     5725  347 1597
18  0.010    0.18 0.25382932 0.23113511 0.25888750     5640  341 1682
19  0.010    0.19 0.26039387 0.24424733 0.44012473     5541  338 1781
20  0.010    0.20 0.27133479 0.26005913 0.60905084     5423  333 1899
21  0.010    0.21 0.28008753 0.26905772 0.62153662     5357  329 1965
22  0.010    0.22 0.30634573 0.28474097 0.31661032     5247  317 2075
23  0.010    0.23 0.32603939 0.29708189 0.17909888     5160  308 2162
24  0.010    0.24 0.34573304 0.31263659 0.12822041     5048  299 2274
25  0.010    0.25 0.35448578 0.32754853 0.22499999     4936  295 2386
26  0.010    0.26 0.37199125 0.34657411 0.26006844     4796  287 2526
27  0.010    0.27 0.38730853 0.36264301 0.27999131     4678  280 2644
28  0.010    0.28 0.39824945 0.37871192 0.40213675     4558  275 2764
29  0.010    0.29 0.40481400 0.39375241 0.65305224     4444  272 2878
30  0.010    0.30 0.42450766 0.41046407 0.56188102     4323  263 2999
31  0.010    0.31 0.43107221 0.42434760 0.80179689     4218  260 3104
32  0.010    0.32 0.43982495 0.43733128 0.95042867     4121  256 3201
33  0.010    0.33 0.45733042 0.45532845 0.96795761     3989  248 3333
34  0.010    0.34 0.47045952 0.47062604 1.00000000     3876  242 3446
35  0.010    0.35 0.47702407 0.48412392 0.79116154     3774  239 3548
36  0.010    0.36 0.49452954 0.49697905 0.95236822     3682  231 3640
37  0.010    0.37 0.52078775 0.51394781 0.80002605     3562  219 3760
38  0.010    0.38 0.53172867 0.53194498 1.00000000     3427  214 3895
39  0.010    0.39 0.55579869 0.55084201 0.86413893     3291  203 4031
40  0.010    0.40 0.56892779 0.56588250 0.93087511     3180  197 4142
41  0.010    0.41 0.58643326 0.58015169 0.81684628     3077  189 4245
42  0.010    0.42 0.60393873 0.59634915 0.77050182     2959  181 4363
43  0.010    0.43 0.60831510 0.61164674 0.91942245     2842  179 4480
44  0.010    0.44 0.61925602 0.62630158 0.78633928     2733  174 4589
45  0.010    0.45 0.63894967 0.64378455 0.86334013     2606  165 4716
46  0.010    0.46 0.64770241 0.65702532 0.70248906     2507  161 4815
47  0.010    0.47 0.66301969 0.67026610 0.77306952     2411  154 4911
48  0.010    0.48 0.67614880 0.68222137 0.81374252     2324  148 4998
49  0.010    0.49 0.70021882 0.69070575 0.68815641     2269  137 5053
50  0.010    0.50 0.70897155 0.70407507 0.85436421     2169  133 5153
51  0.010    0.51 0.72647702 0.71358786 0.56536448     2103  125 5219
52  0.010    0.52 0.74398249 0.72695719 0.43074140     2007  117 5315
53  0.010    0.53 0.74835886 0.73736984 0.62028012     1928  115 5394
54  0.010    0.54 0.75273523 0.74701118 0.81446068     1855  113 5467
55  0.010    0.55 0.76367615 0.75870935 0.84191857     1769  108 5553
56  0.010    0.56 0.77680525 0.76809359 0.69084945     1702  102 5620
57  0.010    0.57 0.77899344 0.77657797 0.94427335     1637  101 5685
58  0.010    0.58 0.79431072 0.78621931 0.70685701     1569   94 5753
59  0.010    0.59 0.79649891 0.79431804 0.95275707     1507   93 5815
60  0.010    0.60 0.80525164 0.80331662 0.96281915     1441   89 5881
61  0.010    0.61 0.80525164 0.81090114 0.79769382     1382   89 5940
62  0.010    0.62 0.82056893 0.81822856 0.94323365     1332   82 5990
63  0.010    0.63 0.82275711 0.82568454 0.91520092     1275   81 6047
64  0.010    0.64 0.83588621 0.83404037 0.96448722     1216   75 6106
65  0.010    0.65 0.84682713 0.84188199 0.81608930     1160   70 6162
66  0.010    0.66 0.85120350 0.84985217 0.98733983     1100   68 6222
67  0.010    0.67 0.85995624 0.85576552 0.84600803     1058   64 6264
68  0.010    0.68 0.86652079 0.86013626 0.73680041     1027   61 6295
69  0.010    0.69 0.86870897 0.86592107 0.91277866      983   60 6339
70  0.010    0.70 0.88183807 0.87273428 0.59640912      936   54 6386
71  0.010    0.71 0.88402626 0.87787633 0.73367825      897   53 6425
72  0.010    0.72 0.89277899 0.88546086 0.66672881      842   49 6480
73  0.010    0.73 0.89277899 0.88996015 0.90334035      807   49 6515
74  0.010    0.74 0.89715536 0.89535930 0.95969778      767   47 6555
75  0.010    0.75 0.90153173 0.90037280 0.99619395      730   45 6592
76  0.010    0.76 0.90590810 0.90461499 0.98808913      699   43 6623
77  0.010    0.77 0.90590810 0.91027124 0.80100717      655   43 6667
78  0.010    0.78 0.91903720 0.91567039 0.85698408      619   37 6703
79  0.010    0.79 0.92341357 0.92016969 0.86125535      586   35 6736
80  0.010    0.80 0.92560175 0.92428333 0.98509224      555   34 6767
81  0.010    0.81 0.92778993 0.92736856 1.00000000      532   33 6790
82  0.010    0.82 0.93435449 0.93238205 0.93856019      496   30 6826
83  0.010    0.83 0.94091904 0.93778121 0.85210646      457   27 6865
84  0.010    0.84 0.94310722 0.94099499 0.92414924      433   26 6889
85  0.010    0.85 0.94748359 0.94433732 0.84364699      409   24 6913
86  0.010    0.86 0.95404814 0.94935082 0.71729648      373   21 6949
87  0.010    0.87 0.95623632 0.95269315 0.79934346      348   20 6974
88  0.010    0.88 0.96061269 0.95732099 0.81066927      314   18 7008
89  0.010    0.89 0.96280088 0.96117753 0.95186042      285   17 7037
90  0.010    0.90 0.96717724 0.96451986 0.85228231      261   15 7061
91  0.010    0.91 0.97155361 0.96696233 0.66636957      244   13 7078
92  0.010    0.92 0.97155361 0.97120453 1.00000000      211   13 7111
93  0.010    0.93 0.97592998 0.97531816 1.00000000      181   11 7141
94  0.010    0.94 0.97592998 0.97814629 0.86569485      159   11 7163
95  0.010    0.95 0.98468271 0.98213138 0.80848152      132    7 7190
96  0.010    0.96 0.98905908 0.98624502 0.74488621      102    5 7220
97  0.010    0.97 0.99124726 0.99010156 0.99083340       73    4 7249
98  0.010    0.98 0.99124726 0.99305823 0.84911228       50    4 7272
99  0.010    0.99 0.99781182 0.99652912 0.94366508       26    1 7296
100 0.010    1.00 1.00000000 1.00000000 0.00000000        0    0 7322
101 0.025    0.01 0.03804348 0.04422162 0.37598698     6550  885  309
102 0.025    0.02 0.05543478 0.05913356 0.66566779     6450  869  409
103 0.025    0.03 0.06195652 0.06710374 0.55227442     6394  863  465
104 0.025    0.04 0.07391304 0.07828770 0.64501779     6318  852  541
105 0.025    0.05 0.08478261 0.08792904 0.76654233     6253  842  606
106 0.025    0.06 0.09891304 0.09949865 0.99637265     6176  829  683
107 0.025    0.07 0.10978261 0.10824013 0.91727608     6118  819  741
108 0.025    0.08 0.12500000 0.11813858 0.52720807     6055  805  804
109 0.025    0.09 0.13695652 0.13022239 0.55239478     5972  794  887
110 0.025    0.10 0.15000000 0.13909243 0.33332115     5915  782  944
111 0.025    0.11 0.15869565 0.14899087 0.40593624     5846  774 1013
112 0.025    0.12 0.17173913 0.16068903 0.35541788     5767  762 1092
113 0.025    0.13 0.17826087 0.17058748 0.54035193     5696  756 1163
114 0.025    0.14 0.19130435 0.18151433 0.43840107     5623  744 1236
115 0.025    0.15 0.20543478 0.19449801 0.39633793     5535  731 1324
116 0.025    0.16 0.21521739 0.20439645 0.41037180     5467  722 1392
117 0.025    0.17 0.23260870 0.21943695 0.32431857     5366  706 1493
118 0.025    0.18 0.24456522 0.23113511 0.32343130     5286  695 1573
119 0.025    0.19 0.25869565 0.24424733 0.29583349     5197  682 1662
120 0.025    0.20 0.27173913 0.26005913 0.41218766     5086  670 1773
121 0.025    0.21 0.27826087 0.26905772 0.52819897     5022  664 1837
122 0.025    0.22 0.29456522 0.28474097 0.50650958     4915  649 1944
123 0.025    0.23 0.30978261 0.29708189 0.39014748     4833  635 2026
124 0.025    0.24 0.32500000 0.31263659 0.41015493     4726  621 2133
125 0.025    0.25 0.33695652 0.32754853 0.54178526     4621  610 2238
126 0.025    0.26 0.35108696 0.34657411 0.78759659     4486  597 2373
127 0.025    0.27 0.36630435 0.36264301 0.83407057     4375  583 2484
128 0.025    0.28 0.38043478 0.37871192 0.93739994     4263  570 2596
129 0.025    0.29 0.38804348 0.39375241 0.73272333     4153  563 2706
130 0.025    0.30 0.40652174 0.41046407 0.82339152     4040  546 2819
131 0.025    0.31 0.42173913 0.42434760 0.89264398     3946  532 2913
132 0.025    0.32 0.42934783 0.43733128 0.62805380     3852  525 3007
133 0.025    0.33 0.44673913 0.45532845 0.60175691     3728  509 3131
134 0.025    0.34 0.45978261 0.47062604 0.50505095     3621  497 3238
135 0.025    0.35 0.46630435 0.48412392 0.26414070     3522  491 3337
136 0.025    0.36 0.47934783 0.49697905 0.26961638     3434  479 3425
137 0.025    0.37 0.50000000 0.51394781 0.38632432     3321  460 3538
138 0.025    0.38 0.50978261 0.53194498 0.16165910     3190  451 3669
139 0.025    0.39 0.53369565 0.55084201 0.28094849     3065  429 3794
140 0.025    0.40 0.54673913 0.56588250 0.22544134     2960  417 3899
141 0.025    0.41 0.56086957 0.58015169 0.22003278     2862  404 3997
142 0.025    0.42 0.58260870 0.59634915 0.38492740     2756  384 4103
143 0.025    0.43 0.59347826 0.61164674 0.24275478     2647  374 4212
144 0.025    0.44 0.60760870 0.62630158 0.22558413     2546  361 4313
145 0.025    0.45 0.62717391 0.64378455 0.27846607     2428  343 4431
146 0.025    0.46 0.63478261 0.65702532 0.13979664     2332  336 4527
147 0.025    0.47 0.64673913 0.67026610 0.11429114     2240  325 4619
148 0.025    0.48 0.65978261 0.68222137 0.12876858     2159  313 4700
149 0.025    0.49 0.67500000 0.69070575 0.28930978     2107  299 4752
150 0.025    0.50 0.68804348 0.70407507 0.27306418     2015  287 4844
151 0.025    0.51 0.70434783 0.71358786 0.53435319     1956  272 4903
152 0.025    0.52 0.71956522 0.72695719 0.61951619     1866  258 4993
153 0.025    0.53 0.72608696 0.73736984 0.43052210     1791  252 5068
154 0.025    0.54 0.73695652 0.74701118 0.47974213     1726  242 5133
155 0.025    0.55 0.75108696 0.75870935 0.59304999     1648  229 5211
156 0.025    0.56 0.75869565 0.76809359 0.49797549     1582  222 5277
157 0.025    0.57 0.76086957 0.77657797 0.23959190     1518  220 5341
158 0.025    0.58 0.77391304 0.78621931 0.35403759     1455  208 5404
159 0.025    0.59 0.77934783 0.79431804 0.24894447     1397  203 5462
160 0.025    0.60 0.79565217 0.80331662 0.56280615     1342  188 5517
161 0.025    0.61 0.79782609 0.81090114 0.30126723     1285  186 5574
162 0.025    0.62 0.81195652 0.81822856 0.63136113     1241  173 5618
163 0.025    0.63 0.81413043 0.82568454 0.34851147     1185  171 5674
164 0.025    0.64 0.82391304 0.83404037 0.40535811     1129  162 5730
165 0.025    0.65 0.83369565 0.84188199 0.49862715     1077  153 5782
166 0.025    0.66 0.84239130 0.84985217 0.53163472     1023  145 5836
167 0.025    0.67 0.84673913 0.85576552 0.43542902      981  141 5878
168 0.025    0.68 0.85434783 0.86013626 0.62522216      954  134 5905
169 0.025    0.69 0.85978261 0.86592107 0.59583361      914  129 5945
170 0.025    0.70 0.87391304 0.87273428 0.95090243      874  116 5985
171 0.025    0.71 0.87608696 0.87787633 0.90217738      836  114 6023
172 0.025    0.72 0.88369565 0.88546086 0.90137951      784  107 6075
173 0.025    0.73 0.88804348 0.88996015 0.88728431      753  103 6106
174 0.025    0.74 0.89347826 0.89535930 0.88774906      716   98 6143
175 0.025    0.75 0.89782609 0.90037280 0.82894780      681   94 6178
176 0.025    0.76 0.90326087 0.90461499 0.92896910      653   89 6206
177 0.025    0.77 0.90869565 0.91027124 0.90713390      614   84 6245
178 0.025    0.78 0.91956522 0.91567039 0.69685498      582   74 6277
179 0.025    0.79 0.92173913 0.92016969 0.90268074      549   72 6310
180 0.025    0.80 0.92282609 0.92428333 0.91116180      518   71 6341
181 0.025    0.81 0.92391304 0.92736856 0.71702494      495   70 6364
182 0.025    0.82 0.92934783 0.93238205 0.74864551      461   65 6398
183 0.025    0.83 0.93478261 0.93778121 0.74267600      424   60 6435
184 0.025    0.84 0.93804348 0.94099499 0.74132231      402   57 6457
185 0.025    0.85 0.94456522 0.94433732 1.00000000      382   51 6477
186 0.025    0.86 0.95000000 0.94935082 0.98757645      348   46 6511
187 0.025    0.87 0.95108696 0.95269315 0.87154416      323   45 6536
188 0.025    0.88 0.95760870 0.95732099 1.00000000      293   39 6566
189 0.025    0.89 0.95978261 0.96117753 0.88678291      265   37 6594
190 0.025    0.90 0.96413043 0.96451986 1.00000000      243   33 6616
191 0.025    0.91 0.96847826 0.96696233 0.86049447      228   29 6631
192 0.025    0.92 0.97282609 0.97120453 0.83504298      199   25 6660
193 0.025    0.93 0.97608696 0.97531816 0.96258615      170   22 6689
194 0.025    0.94 0.97717391 0.97814629 0.92450686      149   21 6710
195 0.025    0.95 0.98478261 0.98213138 0.60729229      125   14 6734
196 0.025    0.96 0.99021739 0.98624502 0.34163041       98    9 6761
197 0.025    0.97 0.99239130 0.99010156 0.56882123       70    7 6789
198 0.025    0.98 0.99456522 0.99305823 0.70777222       49    5 6810
199 0.025    0.99 0.99782609 0.99652912 0.67898675       25    2 6834
200 0.025    1.00 1.00000000 1.00000000 0.00000000        0    0 6859
201 0.050    0.01 0.04294918 0.04422162 0.85435587     6098 1337  284
202 0.050    0.02 0.06156049 0.05913356 0.71737996     6008 1311  374
203 0.050    0.03 0.06800286 0.06710374 0.92887484     5955 1302  427
204 0.050    0.04 0.08088762 0.07828770 0.73053868     5886 1284  496
205 0.050    0.05 0.09090909 0.08792904 0.70240006     5825 1270  557
206 0.050    0.06 0.10236220 0.09949865 0.72977690     5751 1254  631
207 0.050    0.07 0.11166786 0.10824013 0.68346965     5696 1241  686
208 0.050    0.08 0.12598425 0.11813858 0.33842728     5639 1221  743
209 0.050    0.09 0.13815319 0.13022239 0.35313273     5562 1204  820
210 0.050    0.10 0.15175376 0.13909243 0.14233249     5512 1185  870
211 0.050    0.11 0.16105941 0.14899087 0.17474629     5448 1172  934
212 0.050    0.12 0.17394417 0.16068903 0.14728643     5375 1154 1007
213 0.050    0.13 0.17967072 0.17058748 0.33846388     5306 1146 1076
214 0.050    0.14 0.19398712 0.18151433 0.19463166     5241 1126 1141
215 0.050    0.15 0.20758769 0.19449801 0.18439884     5159 1107 1223
216 0.050    0.16 0.21975662 0.20439645 0.12474480     5099 1090 1283
217 0.050    0.17 0.23693629 0.21943695 0.08743056     5006 1066 1376
218 0.050    0.18 0.24982105 0.23113511 0.07280195     4933 1048 1449
219 0.050    0.19 0.26342162 0.24424733 0.07072677     4850 1029 1532
220 0.050    0.20 0.27702219 0.26005913 0.11828051     4746 1010 1636
221 0.050    0.21 0.28274875 0.26905772 0.21473522     4684 1002 1698
222 0.050    0.22 0.30207588 0.28474097 0.12058168     4589  975 1793
223 0.050    0.23 0.31710809 0.29708189 0.07572286     4514  954 1868
224 0.050    0.24 0.33643522 0.31263659 0.03692414     4420  927 1962
225 0.050    0.25 0.34788833 0.32754853 0.07893279     4320  911 2062
226 0.050    0.26 0.36148890 0.34657411 0.20684991     4191  892 2191
227 0.050    0.27 0.37365784 0.36264301 0.36034529     4083  875 2299
228 0.050    0.28 0.39298497 0.37871192 0.23650306     3985  848 2397
229 0.050    0.29 0.40157480 0.39375241 0.52840576     3880  836 2502
230 0.050    0.30 0.41803865 0.41046407 0.54492837     3773  813 2609
231 0.050    0.31 0.43450251 0.42434760 0.41337854     3688  790 2694
232 0.050    0.32 0.44452398 0.43733128 0.56965554     3601  776 2781
233 0.050    0.33 0.46456693 0.45532845 0.46181833     3489  748 2893
234 0.050    0.34 0.48246242 0.47062604 0.34264280     3395  723 2987
235 0.050    0.35 0.48962062 0.48412392 0.67133427     3300  713 3082
236 0.050    0.36 0.50393701 0.49697905 0.58595159     3220  693 3162
237 0.050    0.37 0.52397996 0.51394781 0.42444961     3116  665 3266
238 0.050    0.38 0.53543307 0.53194498 0.79574125     2992  649 3390
239 0.050    0.39 0.55977094 0.55084201 0.47705241     2879  615 3503
240 0.050    0.40 0.57337151 0.56588250 0.55270897     2781  596 3601
241 0.050    0.41 0.58697208 0.58015169 0.58896517     2689  577 3693
242 0.050    0.42 0.60486757 0.59634915 0.49249187     2588  552 3794
243 0.050    0.43 0.61775233 0.61164674 0.62651164     2487  534 3895
244 0.050    0.44 0.63493200 0.62630158 0.48042901     2397  510 3985
245 0.050    0.45 0.64924839 0.64378455 0.65995373     2281  490 4101
246 0.050    0.46 0.65783822 0.65702532 0.96845078     2190  478 4192
247 0.050    0.47 0.66714388 0.67026610 0.80828393     2100  465 4282
248 0.050    0.48 0.67859699 0.68222137 0.77220607     2023  449 4359
249 0.050    0.49 0.69076593 0.69070575 1.00000000     1974  432 4408
250 0.050    0.50 0.70150322 0.70407507 0.84136606     1885  417 4497
251 0.050    0.51 0.71510379 0.71358786 0.91581979     1830  398 4552
252 0.050    0.52 0.73013601 0.72695719 0.79387939     1747  377 4635
253 0.050    0.53 0.73729420 0.73736984 1.00000000     1676  367 4706
254 0.050    0.54 0.74946314 0.74701118 0.84244197     1618  350 4764
255 0.050    0.55 0.76306371 0.75870935 0.69991698     1546  331 4836
256 0.050    0.56 0.77236936 0.76809359 0.70167448     1486  318 4896
257 0.050    0.57 0.77594846 0.77657797 0.97853473     1425  313 4957
258 0.050    0.58 0.78525412 0.78621931 0.95125993     1363  300 5019
259 0.050    0.59 0.79169649 0.79431804 0.81724020     1309  291 5073
260 0.050    0.60 0.80887616 0.80331662 0.58919675     1263  267 5119
261 0.050    0.61 0.81460272 0.81090114 0.72457463     1212  259 5170
262 0.050    0.62 0.82605583 0.81822856 0.42416435     1171  243 5211
263 0.050    0.63 0.83035075 0.82568454 0.63934712     1119  237 5263
264 0.050    0.64 0.83822477 0.83404037 0.67126528     1065  226 5317
265 0.050    0.65 0.84538296 0.84188199 0.72222793     1014  216 5368
266 0.050    0.66 0.85110952 0.84985217 0.91724694      960  208 5422
267 0.050    0.67 0.85612026 0.85576552 1.00000000      921  201 5461
268 0.050    0.68 0.86184681 0.86013626 0.87215120      895  193 5487
269 0.050    0.69 0.86685755 0.86592107 0.94413949      857  186 5525
270 0.050    0.70 0.88045812 0.87273428 0.36174913      823  167 5559
271 0.050    0.71 0.88260558 0.87787633 0.58169622      786  164 5596
272 0.050    0.72 0.88904796 0.88546086 0.67563884      736  155 5646
273 0.050    0.73 0.89191124 0.88996015 0.83360471      705  151 5677
274 0.050    0.74 0.89692198 0.89535930 0.87097642      670  144 5712
275 0.050    0.75 0.90193271 0.90037280 0.86846354      638  137 5744
276 0.050    0.76 0.90765927 0.90461499 0.70589327      613  129 5769
277 0.050    0.77 0.91410165 0.91027124 0.61609974      578  120 5804
278 0.050    0.78 0.92269148 0.91567039 0.32243234      548  108 5834
279 0.050    0.79 0.92555476 0.92016969 0.44403517      517  104 5865
280 0.050    0.80 0.92627058 0.92428333 0.79937705      486  103 5896
281 0.050    0.81 0.92770222 0.92736856 1.00000000      464  101 5918
282 0.050    0.82 0.93342878 0.93238205 0.90987035      433   93 5949
283 0.050    0.83 0.93772369 0.93778121 1.00000000      397   87 5985
284 0.050    0.84 0.94130279 0.94099499 1.00000000      377   82 6005
285 0.050    0.85 0.94774517 0.94433732 0.58304449      360   73 6022
286 0.050    0.86 0.95347173 0.94935082 0.47886128      329   65 6053
287 0.050    0.87 0.95561918 0.95269315 0.61765073      306   62 6076
288 0.050    0.88 0.96134574 0.95732099 0.45411109      278   54 6104
289 0.050    0.89 0.96492484 0.96117753 0.46904266      253   49 6129
290 0.050    0.90 0.96850394 0.96451986 0.41858735      232   44 6150
291 0.050    0.91 0.97136722 0.96696233 0.35013142      217   40 6165
292 0.050    0.92 0.97637795 0.97120453 0.23473558      191   33 6191
293 0.050    0.93 0.97995705 0.97531816 0.25487934      164   28 6218
294 0.050    0.94 0.98138869 0.97814629 0.41557872      144   26 6238
295 0.050    0.95 0.98711525 0.98213138 0.14959493      121   18 6261
296 0.050    0.96 0.99212598 0.98624502 0.05037509       96   11 6286
297 0.050    0.97 0.99427344 0.99010156 0.11188484       69    8 6313
298 0.050    0.98 0.99570508 0.99305823 0.25528324       48    6 6334
299 0.050    0.99 0.99856836 0.99652912 0.23812048       25    2 6357
300 0.050    1.00 1.00000000 1.00000000 0.00000000        0    0 6382
301 0.075    0.01 0.04519774 0.04422162 0.87169726     5745 1690  264
302 0.075    0.02 0.06271186 0.05913356 0.50359084     5660 1659  349
303 0.075    0.03 0.06892655 0.06710374 0.76822817     5609 1648  400
304 0.075    0.04 0.08022599 0.07828770 0.76794708     5542 1628  467
305 0.075    0.05 0.08983051 0.08792904 0.78434695     5484 1611  525
306 0.075    0.06 0.10225989 0.09949865 0.69181274     5416 1589  593
307 0.075    0.07 0.11186441 0.10824013 0.60663517     5365 1572  644
308 0.075    0.08 0.12655367 0.11813858 0.22778117     5314 1546  695
309 0.075    0.09 0.14067797 0.13022239 0.14791122     5245 1521  764
310 0.075    0.10 0.15254237 0.13909243 0.06853713     5197 1500  812
311 0.075    0.11 0.15988701 0.14899087 0.15363565     5133 1487  876
312 0.075    0.12 0.17175141 0.16068903 0.15999152     5063 1466  946
313 0.075    0.13 0.17683616 0.17058748 0.44770191     4995 1457 1014
314 0.075    0.14 0.18983051 0.18151433 0.31842322     4933 1434 1076
315 0.075    0.15 0.20056497 0.19449801 0.48420639     4851 1415 1158
316 0.075    0.16 0.21242938 0.20439645 0.35757170     4795 1394 1214
317 0.075    0.17 0.22994350 0.21943695 0.23699520     4709 1363 1300
318 0.075    0.18 0.24180791 0.23113511 0.23806915     4639 1342 1370
319 0.075    0.19 0.25649718 0.24424733 0.18242027     4563 1316 1446
320 0.075    0.20 0.27062147 0.26005913 0.26196487     4465 1291 1544
321 0.075    0.21 0.27966102 0.26905772 0.26526620     4411 1275 1598
322 0.075    0.22 0.30056497 0.28474097 0.09925384     4326 1238 1683
323 0.075    0.23 0.31581921 0.29708189 0.05321685     4257 1211 1752
324 0.075    0.24 0.33559322 0.31263659 0.01921443     4171 1176 1838
325 0.075    0.25 0.34576271 0.32754853 0.06740792     4073 1158 1936
326 0.075    0.26 0.35932203 0.34657411 0.20988272     3949 1134 2060
327 0.075    0.27 0.37401130 0.36264301 0.26968757     3850 1108 2159
328 0.075    0.28 0.39378531 0.37871192 0.14439320     3760 1073 2249
329 0.075    0.29 0.40451977 0.39375241 0.30430497     3662 1054 2347
330 0.075    0.30 0.42146893 0.41046407 0.29676898     3562 1024 2447
331 0.075    0.31 0.43785311 0.42434760 0.20030984     3483  995 2526
332 0.075    0.32 0.44745763 0.43733128 0.34215917     3399  978 2610
333 0.075    0.33 0.46892655 0.45532845 0.20057718     3297  940 2712
334 0.075    0.34 0.48531073 0.47062604 0.16721694     3207  911 2802
335 0.075    0.35 0.49491525 0.48412392 0.31413315     3119  894 2890
336 0.075    0.36 0.50960452 0.49697905 0.23732648     3045  868 2964
337 0.075    0.37 0.52937853 0.51394781 0.14683463     2948  833 3061
338 0.075    0.38 0.54124294 0.53194498 0.38710661     2829  812 3180
339 0.075    0.39 0.56214689 0.55084201 0.28880652     2719  775 3290
340 0.075    0.40 0.57740113 0.56588250 0.27784637     2629  748 3380
341 0.075    0.41 0.58813559 0.58015169 0.45508385     2537  729 3472
342 0.075    0.42 0.60508475 0.59634915 0.40952581     2441  699 3568
343 0.075    0.43 0.61920904 0.61164674 0.47461133     2347  674 3662
344 0.075    0.44 0.63728814 0.62630158 0.28954653     2265  642 3744
345 0.075    0.45 0.65141243 0.64378455 0.46280464     2154  617 3855
346 0.075    0.46 0.66101695 0.65702532 0.70838714     2068  600 3941
347 0.075    0.47 0.67175141 0.67026610 0.90252348     1984  581 4025
348 0.075    0.48 0.68531073 0.68222137 0.77291269     1915  557 4094
349 0.075    0.49 0.69830508 0.69070575 0.44858674     1872  534 4137
350 0.075    0.50 0.70847458 0.70407507 0.66592499     1786  516 4223
351 0.075    0.51 0.72033898 0.71358786 0.49339380     1733  495 4276
352 0.075    0.52 0.73672316 0.72695719 0.30823479     1658  466 4351
353 0.075    0.53 0.74463277 0.73736984 0.44767116     1591  452 4418
354 0.075    0.54 0.75706215 0.74701118 0.28209591     1538  430 4471
355 0.075    0.55 0.76949153 0.75870935 0.24012654     1469  408 4540
356 0.075    0.56 0.77853107 0.76809359 0.24941753     1412  392 4597
357 0.075    0.57 0.78305085 0.77657797 0.47684005     1354  384 4655
358 0.075    0.58 0.79378531 0.78621931 0.39509275     1298  365 4711
359 0.075    0.59 0.80000000 0.79431804 0.52253280     1246  354 4763
360 0.075    0.60 0.81525424 0.80331662 0.16044381     1203  327 4806
361 0.075    0.61 0.82203390 0.81090114 0.18472243     1156  315 4853
362 0.075    0.62 0.83220339 0.81822856 0.08922223     1117  297 4892
363 0.075    0.63 0.83841808 0.82568454 0.11618059     1070  286 4939
364 0.075    0.64 0.84576271 0.83404037 0.14105238     1018  273 4991
365 0.075    0.65 0.85254237 0.84188199 0.17333311      969  261 5040
366 0.075    0.66 0.85875706 0.84985217 0.24791305      918  250 5091
367 0.075    0.67 0.86384181 0.85576552 0.28827988      881  241 5128
368 0.075    0.68 0.86892655 0.86013626 0.24032943      856  232 5153
369 0.075    0.69 0.87514124 0.86592107 0.20925909      822  221 5187
370 0.075    0.70 0.88700565 0.87273428 0.04451081      790  200 5219
371 0.075    0.71 0.89039548 0.87787633 0.07362583      756  194 5253
372 0.075    0.72 0.89548023 0.88546086 0.14331860      706  185 5303
373 0.075    0.73 0.89774011 0.88996015 0.25144829      675  181 5334
374 0.075    0.74 0.90282486 0.89535930 0.26129594      642  172 5367
375 0.075    0.75 0.90790960 0.90037280 0.24628155      612  163 5397
376 0.075    0.76 0.91242938 0.90461499 0.21967856      587  155 5422
377 0.075    0.77 0.91977401 0.91027124 0.12250816      556  142 5453
378 0.075    0.78 0.92711864 0.91567039 0.05442616      527  129 5482
379 0.075    0.79 0.92994350 0.92016969 0.09367579      497  124 5512
380 0.075    0.80 0.93050847 0.92428333 0.28223992      466  123 5543
381 0.075    0.81 0.93220339 0.92736856 0.40110897      445  120 5564
382 0.075    0.82 0.93672316 0.93238205 0.43908117      414  112 5595
383 0.075    0.83 0.94237288 0.93778121 0.39313375      382  102 5627
384 0.075    0.84 0.94576271 0.94099499 0.36221075      363   96 5646
385 0.075    0.85 0.95141243 0.94433732 0.15613053      347   86 5662
386 0.075    0.86 0.95593220 0.94935082 0.16912170      316   78 5693
387 0.075    0.87 0.95819209 0.95269315 0.23951143      294   74 5715
388 0.075    0.88 0.96327684 0.95732099 0.17909613      267   65 5742
389 0.075    0.89 0.96610169 0.96117753 0.25005514      242   60 5767
390 0.075    0.90 0.96949153 0.96451986 0.22498553      222   54 5787
391 0.075    0.91 0.97231638 0.96696233 0.17438423      208   49 5801
392 0.075    0.92 0.97683616 0.97120453 0.12573514      183   41 5826
393 0.075    0.93 0.98079096 0.97531816 0.10930547      158   34 5851
394 0.075    0.94 0.98192090 0.97814629 0.25290014      138   32 5871
395 0.075    0.95 0.98644068 0.98213138 0.14565484      115   24 5894
396 0.075    0.96 0.99096045 0.98624502 0.06847458       91   16 5918
397 0.075    0.97 0.99378531 0.99010156 0.10004857       66   11 5943
398 0.075    0.98 0.99491525 0.99305823 0.36399814       45    9 5964
399 0.075    0.99 0.99830508 0.99652912 0.22414616       24    3 5985
400 0.075    1.00 1.00000000 1.00000000 0.00000000        0    0 6009
401 0.100    0.01 0.04588910 0.04422162 0.71012595     5439 1996  248
402 0.100    0.02 0.06214149 0.05913356 0.53003141     5357 1962  330
403 0.100    0.03 0.06931166 0.06710374 0.67378597     5310 1947  377
404 0.100    0.04 0.08078394 0.07828770 0.65306816     5247 1923  440
405 0.100    0.05 0.09034417 0.08792904 0.68102936     5192 1903  495
406 0.100    0.06 0.10277247 0.09949865 0.58757546     5128 1877  559
407 0.100    0.07 0.11137667 0.10824013 0.61785148     5078 1859  609
408 0.100    0.08 0.12571702 0.11813858 0.22384199     5031 1829  656
409 0.100    0.09 0.14005736 0.13022239 0.12719531     4967 1799  720
410 0.100    0.10 0.15152964 0.13909243 0.05933870     4922 1775  765
411 0.100    0.11 0.15869981 0.14899087 0.15483491     4860 1760  827
412 0.100    0.12 0.17112811 0.16068903 0.13734180     4795 1734  892
413 0.100    0.13 0.17782027 0.17058748 0.31992424     4732 1720  955
414 0.100    0.14 0.18977055 0.18151433 0.26585318     4672 1695 1015
415 0.100    0.15 0.20076482 0.19449801 0.41527443     4594 1672 1093
416 0.100    0.16 0.21271511 0.20439645 0.28381571     4542 1647 1145
417 0.100    0.17 0.22944551 0.21943695 0.20667939     4460 1612 1227
418 0.100    0.18 0.23996176 0.23113511 0.27583390     4391 1590 1296
419 0.100    0.19 0.25525813 0.24424733 0.17986495     4321 1558 1366
420 0.100    0.20 0.26912046 0.26005913 0.28199699     4227 1529 1460
421 0.100    0.21 0.27772467 0.26905772 0.30933464     4175 1511 1512
422 0.100    0.22 0.29780115 0.28474097 0.12857379     4095 1469 1592
423 0.100    0.23 0.31548757 0.29708189 0.03345318     4036 1432 1651
424 0.100    0.24 0.33365201 0.31263659 0.01650737     3953 1394 1734
425 0.100    0.25 0.34464627 0.32754853 0.05465896     3860 1371 1827
426 0.100    0.26 0.35946463 0.34657411 0.15498091     3743 1340 1944
427 0.100    0.27 0.37762906 0.36264301 0.10082371     3656 1302 2031
428 0.100    0.28 0.39674952 0.37871192 0.04966422     3571 1262 2116
429 0.100    0.29 0.40726577 0.39375241 0.14611935     3476 1240 2211
430 0.100    0.30 0.42351816 0.41046407 0.16344630     3380 1206 2307
431 0.100    0.31 0.44072658 0.42434760 0.08065836     3308 1170 2379
432 0.100    0.32 0.45124283 0.43733128 0.14037066     3229 1148 2458
433 0.100    0.33 0.47179732 0.45532845 0.08127123     3132 1105 2555
434 0.100    0.34 0.48661568 0.47062604 0.09140579     3044 1074 2643
435 0.100    0.35 0.49617591 0.48412392 0.20606028     2959 1054 2728
436 0.100    0.36 0.51003824 0.49697905 0.17018210     2888 1025 2799
437 0.100    0.37 0.52724665 0.51394781 0.16217993     2792  989 2895
438 0.100    0.38 0.53919694 0.53194498 0.45215257     2677  964 3010
439 0.100    0.39 0.56022945 0.55084201 0.32518296     2574  920 3113
440 0.100    0.40 0.57600382 0.56588250 0.28616203     2490  887 3197
441 0.100    0.41 0.58795411 0.58015169 0.41233645     2404  862 3283
442 0.100    0.42 0.60372849 0.59634915 0.43626579     2311  829 3376
443 0.100    0.43 0.61902486 0.61164674 0.43328870     2224  797 3463
444 0.100    0.44 0.63718929 0.62630158 0.23901262     2148  759 3539
445 0.100    0.45 0.65057361 0.64378455 0.46436540     2040  731 3647
446 0.100    0.46 0.66061185 0.65702532 0.70600491     1958  710 3729
447 0.100    0.47 0.67256214 0.67026610 0.81493417     1880  685 3807
448 0.100    0.48 0.68594646 0.68222137 0.68877986     1815  657 3872
449 0.100    0.49 0.69837476 0.69070575 0.38983321     1775  631 3912
450 0.100    0.50 0.70984704 0.70407507 0.51671168     1695  607 3992
451 0.100    0.51 0.72131931 0.71358786 0.37531926     1645  583 4042
452 0.100    0.52 0.73709369 0.72695719 0.23468249     1574  550 4113
453 0.100    0.53 0.74474187 0.73736984 0.38589733     1509  534 4178
454 0.100    0.54 0.75621415 0.74701118 0.27001474     1458  510 4229
455 0.100    0.55 0.76720841 0.75870935 0.30174181     1390  487 4297
456 0.100    0.56 0.77533461 0.76809359 0.37481806     1334  470 4353
457 0.100    0.57 0.77915870 0.77657797 0.76361763     1276  462 4411
458 0.100    0.58 0.79063098 0.78621931 0.58613174     1225  438 4462
459 0.100    0.59 0.79780115 0.79431804 0.66767621     1177  423 4510
460 0.100    0.60 0.81214149 0.80331662 0.24789884     1137  393 4550
461 0.100    0.61 0.81835564 0.81090114 0.32428724     1091  380 4596
462 0.100    0.62 0.82743786 0.81822856 0.21340784     1053  361 4634
463 0.100    0.63 0.83508604 0.82568454 0.19638022     1011  345 4676
464 0.100    0.64 0.84273423 0.83404037 0.22411407      962  329 4725
465 0.100    0.65 0.85086042 0.84188199 0.20007085      918  312 4769
466 0.100    0.66 0.85755258 0.84985217 0.26384303      870  298 4817
467 0.100    0.67 0.86281071 0.85576552 0.30005435      835  287 4852
468 0.100    0.68 0.86806883 0.86013626 0.23539824      812  276 4875
469 0.100    0.69 0.87428298 0.86592107 0.20222299      780  263 4907
470 0.100    0.70 0.88432122 0.87273428 0.06853599      748  242 4939
471 0.100    0.71 0.88957935 0.87787633 0.06107832      719  231 4968
472 0.100    0.72 0.89435946 0.88546086 0.14578574      670  221 5017
473 0.100    0.73 0.89674952 0.88996015 0.26283635      640  216 5047
474 0.100    0.74 0.90105163 0.89535930 0.34056771      607  207 5080
475 0.100    0.75 0.90630975 0.90037280 0.30882099      579  196 5108
476 0.100    0.76 0.91061185 0.90461499 0.29438405      555  187 5132
477 0.100    0.77 0.91826004 0.91027124 0.14689862      527  171 5160
478 0.100    0.78 0.92590822 0.91567039 0.05425178      501  155 5186
479 0.100    0.79 0.92829828 0.92016969 0.11942893      471  150 5216
480 0.100    0.80 0.92925430 0.92428333 0.33864201      441  148 5246
481 0.100    0.81 0.93164436 0.92736856 0.40538060      422  143 5265
482 0.100    0.82 0.93690249 0.93238205 0.36169494      394  132 5293
483 0.100    0.83 0.94311663 0.93778121 0.25905016      365  119 5322
484 0.100    0.84 0.94694073 0.94099499 0.19513419      348  111 5339
485 0.100    0.85 0.95267686 0.94433732 0.05875351      334   99 5353
486 0.100    0.86 0.95745698 0.94935082 0.05495953      305   89 5382
487 0.100    0.87 0.95984704 0.95269315 0.08143883      284   84 5403
488 0.100    0.88 0.96462715 0.95732099 0.06144314      258   74 5429
489 0.100    0.89 0.96749522 0.96117753 0.09231266      234   68 5453
490 0.100    0.90 0.97084130 0.96451986 0.07860201      215   61 5472
491 0.100    0.91 0.97370937 0.96696233 0.05144064      202   55 5485
492 0.100    0.92 0.97753346 0.97120453 0.05141121      177   47 5510
493 0.100    0.93 0.98135755 0.97531816 0.04551724      153   39 5534
494 0.100    0.94 0.98231358 0.97814629 0.15064078      133   37 5554
495 0.100    0.95 0.98613767 0.98213138 0.12819855      110   29 5577
496 0.100    0.96 0.99091778 0.98624502 0.04171606       88   19 5599
497 0.100    0.97 0.99378585 0.99010156 0.06264913       64   13 5623
498 0.100    0.98 0.99474187 0.99305823 0.35197885       43   11 5644
499 0.100    0.99 0.99808795 0.99652912 0.22995331       23    4 5664
500 0.100    1.00 1.00000000 1.00000000 0.00000000        0    0 5687
    Dboth
1      17
2      25
3      29
4      34
5      39
6      46
7      51
8      59
9      64
10     72
11     76
12     83
13     86
14     91
15     97
16    102
17    110
18    116
19    119
20    124
21    128
22    140
23    149
24    158
25    162
26    170
27    177
28    182
29    185
30    194
31    197
32    201
33    209
34    215
35    218
36    226
37    238
38    243
39    254
40    260
41    268
42    276
43    278
44    283
45    292
46    296
47    303
48    309
49    320
50    324
51    332
52    340
53    342
54    344
55    349
56    355
57    356
58    363
59    364
60    368
61    368
62    375
63    376
64    382
65    387
66    389
67    393
68    396
69    397
70    403
71    404
72    408
73    408
74    410
75    412
76    414
77    414
78    420
79    422
80    423
81    424
82    427
83    430
84    431
85    433
86    436
87    437
88    439
89    440
90    442
91    444
92    444
93    446
94    446
95    450
96    452
97    453
98    453
99    456
100   457
101    35
102    51
103    57
104    68
105    78
106    91
107   101
108   115
109   126
110   138
111   146
112   158
113   164
114   176
115   189
116   198
117   214
118   225
119   238
120   250
121   256
122   271
123   285
124   299
125   310
126   323
127   337
128   350
129   357
130   374
131   388
132   395
133   411
134   423
135   429
136   441
137   460
138   469
139   491
140   503
141   516
142   536
143   546
144   559
145   577
146   584
147   595
148   607
149   621
150   633
151   648
152   662
153   668
154   678
155   691
156   698
157   700
158   712
159   717
160   732
161   734
162   747
163   749
164   758
165   767
166   775
167   779
168   786
169   791
170   804
171   806
172   813
173   817
174   822
175   826
176   831
177   836
178   846
179   848
180   849
181   850
182   855
183   860
184   863
185   869
186   874
187   875
188   881
189   883
190   887
191   891
192   895
193   898
194   899
195   906
196   911
197   913
198   915
199   918
200   920
201    60
202    86
203    95
204   113
205   127
206   143
207   156
208   176
209   193
210   212
211   225
212   243
213   251
214   271
215   290
216   307
217   331
218   349
219   368
220   387
221   395
222   422
223   443
224   470
225   486
226   505
227   522
228   549
229   561
230   584
231   607
232   621
233   649
234   674
235   684
236   704
237   732
238   748
239   782
240   801
241   820
242   845
243   863
244   887
245   907
246   919
247   932
248   948
249   965
250   980
251   999
252  1020
253  1030
254  1047
255  1066
256  1079
257  1084
258  1097
259  1106
260  1130
261  1138
262  1154
263  1160
264  1171
265  1181
266  1189
267  1196
268  1204
269  1211
270  1230
271  1233
272  1242
273  1246
274  1253
275  1260
276  1268
277  1277
278  1289
279  1293
280  1294
281  1296
282  1304
283  1310
284  1315
285  1324
286  1332
287  1335
288  1343
289  1348
290  1353
291  1357
292  1364
293  1369
294  1371
295  1379
296  1386
297  1389
298  1391
299  1395
300  1397
301    80
302   111
303   122
304   142
305   159
306   181
307   198
308   224
309   249
310   270
311   283
312   304
313   313
314   336
315   355
316   376
317   407
318   428
319   454
320   479
321   495
322   532
323   559
324   594
325   612
326   636
327   662
328   697
329   716
330   746
331   775
332   792
333   830
334   859
335   876
336   902
337   937
338   958
339   995
340  1022
341  1041
342  1071
343  1096
344  1128
345  1153
346  1170
347  1189
348  1213
349  1236
350  1254
351  1275
352  1304
353  1318
354  1340
355  1362
356  1378
357  1386
358  1405
359  1416
360  1443
361  1455
362  1473
363  1484
364  1497
365  1509
366  1520
367  1529
368  1538
369  1549
370  1570
371  1576
372  1585
373  1589
374  1598
375  1607
376  1615
377  1628
378  1641
379  1646
380  1647
381  1650
382  1658
383  1668
384  1674
385  1684
386  1692
387  1696
388  1705
389  1710
390  1716
391  1721
392  1729
393  1736
394  1738
395  1746
396  1754
397  1759
398  1761
399  1767
400  1770
401    96
402   130
403   145
404   169
405   189
406   215
407   233
408   263
409   293
410   317
411   332
412   358
413   372
414   397
415   420
416   445
417   480
418   502
419   534
420   563
421   581
422   623
423   660
424   698
425   721
426   752
427   790
428   830
429   852
430   886
431   922
432   944
433   987
434  1018
435  1038
436  1067
437  1103
438  1128
439  1172
440  1205
441  1230
442  1263
443  1295
444  1333
445  1361
446  1382
447  1407
448  1435
449  1461
450  1485
451  1509
452  1542
453  1558
454  1582
455  1605
456  1622
457  1630
458  1654
459  1669
460  1699
461  1712
462  1731
463  1747
464  1763
465  1780
466  1794
467  1805
468  1816
469  1829
470  1850
471  1861
472  1871
473  1876
474  1885
475  1896
476  1905
477  1921
478  1937
479  1942
480  1944
481  1949
482  1960
483  1973
484  1981
485  1993
486  2003
487  2008
488  2018
489  2024
490  2031
491  2037
492  2045
493  2053
494  2055
495  2063
496  2073
497  2079
498  2081
499  2088
500  2092
enrichment.plotter(gene.hic.filt, "median_FDR.H", "adj.P.Val", "Median FDR of Hi-C Contacts Overlapping Gene, Human")
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp     chisq.p Dneither   DE DHiC
1   0.010    0.01 0.02340426 0.02099433 0.833659804     7142  459  152
2   0.010    0.02 0.02765957 0.02743431 1.000000000     7094  457  200
3   0.010    0.03 0.03191489 0.02910871 0.816678531     7083  455  211
4   0.010    0.04 0.03617021 0.03232870 0.725390082     7060  453  234
5   0.010    0.05 0.03829787 0.03464709 0.751707478     7043  452  251
6   0.010    0.06 0.04468085 0.03735188 0.459901633     7025  449  269
7   0.010    0.07 0.04680851 0.03915507 0.447323621     7012  448  282
8   0.010    0.08 0.05319149 0.04070067 0.195841919     7003  445  291
9   0.010    0.09 0.05957447 0.04211747 0.067923863     6995  442  299
10  0.010    0.10 0.05957447 0.04314786 0.090812369     6987  442  307
11  0.010    0.11 0.06382979 0.04456466 0.048501670     6978  440  316
12  0.010    0.12 0.06382979 0.04662545 0.086839349     6962  440  332
13  0.010    0.13 0.06595745 0.04752705 0.067897566     6956  439  338
14  0.010    0.14 0.06595745 0.04829985 0.083427659     6950  439  344
15  0.010    0.15 0.06808511 0.05010304 0.082815724     6937  438  357
16  0.010    0.16 0.07446809 0.05280783 0.039414320     6919  435  375
17  0.010    0.17 0.07872340 0.05577022 0.032880085     6898  433  396
18  0.010    0.18 0.07872340 0.05692942 0.045380555     6889  433  405
19  0.010    0.19 0.07872340 0.05989181 0.093968894     6866  433  428
20  0.010    0.20 0.08085106 0.06272540 0.115508670     6845  432  449
21  0.010    0.21 0.08297872 0.06555899 0.139392436     6824  431  470
22  0.010    0.22 0.08510638 0.06890778 0.181400672     6799  430  495
23  0.010    0.23 0.08936170 0.07122617 0.137648595     6783  428  511
24  0.010    0.24 0.09574468 0.07444616 0.084674815     6761  425  533
25  0.010    0.25 0.09787234 0.07766615 0.109660441     6737  424  557
26  0.010    0.26 0.09787234 0.08088614 0.191499773     6712  424  582
27  0.010    0.27 0.09787234 0.08397733 0.300779214     6688  424  606
28  0.010    0.28 0.10851064 0.08925811 0.153613186     6652  419  642
29  0.010    0.29 0.11489362 0.09312210 0.110976109     6625  416  669
30  0.010    0.30 0.11702128 0.09763009 0.167248766     6591  415  703
31  0.010    0.31 0.11914894 0.10110768 0.207811386     6565  414  729
32  0.010    0.32 0.12340426 0.10432767 0.187504334     6542  412  752
33  0.010    0.33 0.12765957 0.11038125 0.247131581     6497  410  797
34  0.010    0.34 0.12978723 0.11591963 0.371008008     6455  409  839
35  0.010    0.35 0.13829787 0.12313241 0.337106496     6403  405  891
36  0.010    0.36 0.14468085 0.12995878 0.363607710     6353  402  941
37  0.010    0.37 0.15957447 0.13691396 0.159955390     6306  395  988
38  0.010    0.38 0.16382979 0.14502834 0.259876354     6245  393 1049
39  0.010    0.39 0.17234043 0.15262751 0.246098026     6190  389 1104
40  0.010    0.40 0.18297872 0.15984029 0.177870256     6139  384 1155
41  0.010    0.41 0.19148936 0.16834106 0.186780005     6077  380 1217
42  0.010    0.42 0.20851064 0.17851623 0.091071959     6006  372 1288
43  0.010    0.43 0.21489362 0.18572901 0.106044837     5953  369 1341
44  0.010    0.44 0.22340426 0.19448738 0.115491701     5889  365 1405
45  0.010    0.45 0.23617021 0.20672334 0.116953068     5800  359 1494
46  0.010    0.46 0.24255319 0.21612571 0.168110253     5730  356 1564
47  0.010    0.47 0.25957447 0.22784647 0.102010183     5647  348 1647
48  0.010    0.48 0.27021277 0.23647604 0.085459047     5585  343 1709
49  0.010    0.49 0.28510638 0.24742401 0.057685956     5507  336 1787
50  0.010    0.50 0.30212766 0.26146316 0.043834233     5406  328 1888
51  0.010    0.51 0.31914894 0.27472952 0.029821204     5311  320 1983
52  0.010    0.52 0.33191489 0.28619268 0.027105254     5228  314 2066
53  0.010    0.53 0.34680851 0.29933024 0.023397111     5133  307 2161
54  0.010    0.54 0.35744681 0.31259660 0.034621433     5035  302 2259
55  0.010    0.55 0.37021277 0.32599176 0.039462634     4937  296 2357
56  0.010    0.56 0.38723404 0.33977331 0.028446598     4838  288 2456
57  0.010    0.57 0.40638298 0.35561566 0.020212639     4724  279 2570
58  0.010    0.58 0.42978723 0.37107161 0.007601680     4615  268 2679
59  0.010    0.59 0.43829787 0.38588357 0.018304990     4504  264 2790
60  0.010    0.60 0.45957447 0.40211231 0.010090452     4388  254 2906
61  0.010    0.61 0.47659574 0.41666667 0.007570726     4283  246 3011
62  0.010    0.62 0.48936170 0.43611540 0.018591266     4138  240 3156
63  0.010    0.63 0.51702128 0.45749614 0.008672141     3985  227 3309
64  0.010    0.64 0.52978723 0.47707367 0.020726076     3839  221 3455
65  0.010    0.65 0.54255319 0.49497682 0.037451999     3706  215 3588
66  0.010    0.66 0.55744681 0.51481195 0.062820556     3559  208 3735
67  0.010    0.67 0.57659574 0.53310149 0.057137124     3426  199 3868
68  0.010    0.68 0.60000000 0.55074704 0.030243434     3300  188 3994
69  0.010    0.69 0.61489362 0.56826378 0.039626457     3171  181 4123
70  0.010    0.70 0.64468085 0.58990211 0.014577899     3017  167 4277
71  0.010    0.71 0.67021277 0.60754766 0.004776590     2892  155 4402
72  0.010    0.72 0.68085106 0.63060278 0.022645993     2718  150 4576
73  0.010    0.73 0.69787234 0.65236991 0.036870295     2557  142 4737
74  0.010    0.74 0.70638298 0.67014426 0.094251866     2423  138 4871
75  0.010    0.75 0.72340426 0.68920659 0.109312814     2283  130 5011
76  0.010    0.76 0.75531915 0.70955693 0.027644096     2140  115 5154
77  0.010    0.77 0.76382979 0.72964967 0.095366188     1988  111 5306
78  0.010    0.78 0.79148936 0.75115920 0.042211141     1834   98 5460
79  0.010    0.79 0.81063830 0.76944874 0.033099364     1701   89 5593
80  0.010    0.80 0.82553191 0.78696548 0.040496522     1572   82 5722
81  0.010    0.81 0.83829787 0.80667182 0.083451286     1425   76 5869
82  0.010    0.82 0.85106383 0.82457496 0.134853016     1292   70 6002
83  0.010    0.83 0.87234043 0.84067491 0.061450082     1177   60 6117
84  0.010    0.84 0.88936170 0.85806285 0.052646261     1050   52 6244
85  0.010    0.85 0.89574468 0.87287481 0.143145290      938   49 6356
86  0.010    0.86 0.91702128 0.88794436 0.046992298      831   39 6463
87  0.010    0.87 0.93404255 0.90056672 0.015407715      741   31 6553
88  0.010    0.88 0.94468085 0.91228748 0.013240685      655   26 6639
89  0.010    0.89 0.94680851 0.92490984 0.077009517      558   25 6736
90  0.010    0.90 0.95744681 0.93495621 0.051965268      485   20 6809
91  0.010    0.91 0.95957447 0.94345698 0.144893507      420   19 6874
92  0.010    0.92 0.96595745 0.95337455 0.221695238      346   16 6948
93  0.010    0.93 0.97446809 0.96161772 0.169990509      286   12 7008
94  0.010    0.94 0.97872340 0.96831530 0.232782554      236   10 7058
95  0.010    0.95 0.98936170 0.97514168 0.058753603      188    5 7106
96  0.010    0.96 0.99361702 0.98261206 0.088924349      132    3 7162
97  0.010    0.97 0.99361702 0.98737764 0.299763968       95    3 7199
98  0.010    0.98 0.99361702 0.99149923 0.797349469       63    3 7231
99  0.010    0.99 0.99787234 0.99600721 0.776252403       30    1 7264
100 0.010    1.00 1.00000000 1.00000000 0.000000000        0    0 7294
101 0.025    0.01 0.01733478 0.02099433 0.481511738     6694  907  147
102 0.025    0.02 0.02383532 0.02743431 0.544662978     6650  901  191
103 0.025    0.03 0.02708559 0.02910871 0.775485276     6640  898  201
104 0.025    0.04 0.03033586 0.03232870 0.790593411     6618  895  223
105 0.025    0.05 0.03250271 0.03464709 0.776694448     6602  893  239
106 0.025    0.06 0.03791983 0.03735188 0.996427247     6586  888  255
107 0.025    0.07 0.03900325 0.03915507 1.000000000     6573  887  268
108 0.025    0.08 0.04225352 0.04070067 0.868454719     6564  884  277
109 0.025    0.09 0.04658722 0.04211747 0.526763518     6557  880  284
110 0.025    0.10 0.04658722 0.04314786 0.644398176     6549  880  292
111 0.025    0.11 0.04983749 0.04456466 0.458037970     6541  877  300
112 0.025    0.12 0.05092091 0.04662545 0.564451026     6526  876  315
113 0.025    0.13 0.05200433 0.04752705 0.549385926     6520  875  321
114 0.025    0.14 0.05200433 0.04829985 0.633040562     6514  875  327
115 0.025    0.15 0.05308776 0.05010304 0.717022059     6501  874  340
116 0.025    0.16 0.05633803 0.05280783 0.665392074     6483  871  358
117 0.025    0.17 0.05850488 0.05577022 0.757098193     6462  869  379
118 0.025    0.18 0.06067172 0.05692942 0.654825803     6455  867  386
119 0.025    0.19 0.06175515 0.05989181 0.856941800     6433  866  408
120 0.025    0.20 0.06717226 0.06272540 0.602175328     6416  861  425
121 0.025    0.21 0.07258938 0.06555899 0.396163613     6399  856  442
122 0.025    0.22 0.07475623 0.06890778 0.497720887     6375  854  466
123 0.025    0.23 0.07908992 0.07122617 0.356849449     6361  850  480
124 0.025    0.24 0.08234020 0.07444616 0.364650839     6339  847  502
125 0.025    0.25 0.08342362 0.07766615 0.528219381     6315  846  526
126 0.025    0.26 0.08450704 0.08088614 0.714731230     6291  845  550
127 0.025    0.27 0.08667389 0.08397733 0.801459790     6269  843  572
128 0.025    0.28 0.09425785 0.08925811 0.612811951     6235  836  606
129 0.025    0.29 0.09967497 0.09312210 0.503185757     6210  831  631
130 0.025    0.30 0.10400867 0.09763009 0.524468591     6179  827  662
131 0.025    0.31 0.10725894 0.10110768 0.547017769     6155  824  686
132 0.025    0.32 0.11159263 0.10432767 0.476557087     6134  820  707
133 0.025    0.33 0.11700975 0.11038125 0.529565173     6092  815  749
134 0.025    0.34 0.12351029 0.11591963 0.476054547     6055  809  786
135 0.025    0.35 0.12892741 0.12313241 0.604847182     6004  804  837
136 0.025    0.36 0.13217768 0.12995878 0.871752414     5954  801  887
137 0.025    0.37 0.14301192 0.13691396 0.600879947     5910  791  931
138 0.025    0.38 0.15059588 0.14502834 0.644121140     5854  784  987
139 0.025    0.39 0.16251354 0.15262751 0.400367564     5806  773 1035
140 0.025    0.40 0.17009751 0.15984029 0.390851028     5757  766 1084
141 0.025    0.41 0.17876490 0.16834106 0.392659762     5699  758 1142
142 0.025    0.42 0.19284940 0.17851623 0.243769379     5633  745 1208
143 0.025    0.43 0.19934995 0.18572901 0.276359885     5583  739 1258
144 0.025    0.44 0.20585049 0.19448738 0.376220336     5521  733 1320
145 0.025    0.45 0.21668472 0.20672334 0.451535768     5436  723 1405
146 0.025    0.46 0.22318527 0.21612571 0.608286615     5369  717 1472
147 0.025    0.47 0.23943662 0.22784647 0.393917808     5293  702 1548
148 0.025    0.48 0.24918743 0.23647604 0.353950656     5235  693 1606
149 0.025    0.49 0.26218852 0.24742401 0.286073605     5162  681 1679
150 0.025    0.50 0.28060672 0.26146316 0.170659460     5070  664 1771
151 0.025    0.51 0.30010834 0.27472952 0.071723473     4985  646 1856
152 0.025    0.52 0.31310943 0.28619268 0.058935516     4908  634 1933
153 0.025    0.53 0.33044420 0.29933024 0.030724382     4822  618 2019
154 0.025    0.54 0.34236186 0.31259660 0.041308846     4730  607 2111
155 0.025    0.55 0.35319610 0.32599176 0.065623348     4636  597 2205
156 0.025    0.56 0.36944745 0.33977331 0.046507054     4544  582 2297
157 0.025    0.57 0.38786566 0.35561566 0.032045223     4438  565 2403
158 0.025    0.58 0.40628386 0.37107161 0.020189022     4335  548 2506
159 0.025    0.59 0.41495125 0.38588357 0.057883648     4228  540 2613
160 0.025    0.60 0.43661972 0.40211231 0.024959636     4122  520 2719
161 0.025    0.61 0.45070423 0.41666667 0.027879083     4022  507 2819
162 0.025    0.62 0.46912243 0.43611540 0.034100118     3888  490 2953
163 0.025    0.63 0.48754063 0.45749614 0.055277462     3739  473 3102
164 0.025    0.64 0.50054171 0.47707367 0.137381855     3599  461 3242
165 0.025    0.65 0.51679307 0.49497682 0.168451539     3475  446 3366
166 0.025    0.66 0.53196100 0.51481195 0.282157666     3335  432 3506
167 0.025    0.67 0.54496208 0.53310149 0.462768663     3205  420 3636
168 0.025    0.68 0.56771398 0.55074704 0.285185102     3089  399 3752
169 0.025    0.69 0.58504875 0.56826378 0.288515129     2969  383 3872
170 0.025    0.70 0.60888407 0.58990211 0.224963174     2823  361 4018
171 0.025    0.71 0.63380282 0.60754766 0.088314449     2709  338 4132
172 0.025    0.72 0.64897075 0.63060278 0.231924445     2544  324 4297
173 0.025    0.73 0.67172264 0.65236991 0.201083791     2396  303 4445
174 0.025    0.74 0.68364030 0.67014426 0.372516288     2269  292 4572
175 0.025    0.75 0.70205850 0.68920659 0.389308890     2138  275 4703
176 0.025    0.76 0.72806067 0.70955693 0.200332523     2004  251 4837
177 0.025    0.77 0.73997833 0.72964967 0.475722608     1859  240 4982
178 0.025    0.78 0.76273023 0.75115920 0.408992139     1713  219 5128
179 0.025    0.79 0.78223185 0.76944874 0.346869417     1589  201 5252
180 0.025    0.80 0.79631636 0.78696548 0.486221503     1466  188 5375
181 0.025    0.81 0.80390033 0.80667182 0.854996567     1320  181 5521
182 0.025    0.82 0.83098592 0.82457496 0.617451889     1206  156 5635
183 0.025    0.83 0.84507042 0.84067491 0.733243885     1094  143 5747
184 0.025    0.84 0.86673889 0.85806285 0.450612948      979  123 5862
185 0.025    0.85 0.88082340 0.87287481 0.471734190      877  110 5964
186 0.025    0.86 0.90249187 0.88794436 0.150694157      780   90 6061
187 0.025    0.87 0.91982665 0.90056672 0.042915472      698   74 6143
188 0.025    0.88 0.93174431 0.91228748 0.030449437      618   63 6223
189 0.025    0.89 0.93932828 0.92490984 0.088337109      527   56 6314
190 0.025    0.90 0.94907909 0.93495621 0.074672476      458   47 6383
191 0.025    0.91 0.95882990 0.94345698 0.037681027      401   38 6440
192 0.025    0.92 0.96533044 0.95337455 0.079738257      330   32 6511
193 0.025    0.93 0.97183099 0.96161772 0.103239761      272   26 6569
194 0.025    0.94 0.97724810 0.96831530 0.121023881      225   21 6616
195 0.025    0.95 0.98483207 0.97514168 0.057192973      179   14 6662
196 0.025    0.96 0.99024919 0.98261206 0.078935050      126    9 6715
197 0.025    0.97 0.99241603 0.98737764 0.192349758       91    7 6750
198 0.025    0.98 0.99349946 0.99149923 0.607121665       60    6 6781
199 0.025    0.99 0.99674973 0.99600721 0.917915743       28    3 6813
200 0.025    1.00 1.00000000 1.00000000 0.000000000        0    0 6841
201 0.050    0.01 0.01927195 0.02099433 0.693727342     6227 1374  136
202 0.050    0.02 0.02569593 0.02743431 0.726577541     6186 1365  177
203 0.050    0.03 0.02783726 0.02910871 0.822034197     6176 1362  187
204 0.050    0.04 0.03069236 0.03232870 0.764875100     6155 1358  208
205 0.050    0.05 0.03283369 0.03464709 0.741942430     6140 1355  223
206 0.050    0.06 0.03640257 0.03735188 0.897220531     6124 1350  239
207 0.050    0.07 0.03711635 0.03915507 0.719965435     6111 1349  252
208 0.050    0.08 0.03997145 0.04070067 0.937900904     6103 1345  260
209 0.050    0.09 0.04282655 0.04211747 0.942204788     6096 1341  267
210 0.050    0.10 0.04425410 0.04314786 0.878807488     6090 1339  273
211 0.050    0.11 0.04710921 0.04456466 0.661136815     6083 1335  280
212 0.050    0.12 0.04925054 0.04662545 0.656461714     6070 1332  293
213 0.050    0.13 0.04996431 0.04752705 0.686011234     6064 1331  299
214 0.050    0.14 0.04996431 0.04829985 0.800917717     6058 1331  305
215 0.050    0.15 0.05067809 0.05010304 0.967019974     6045 1330  318
216 0.050    0.16 0.05424697 0.05280783 0.841423215     6029 1325  334
217 0.050    0.17 0.05781585 0.05577022 0.760925638     6011 1320  352
218 0.050    0.18 0.05995717 0.05692942 0.633655788     6005 1317  358
219 0.050    0.19 0.06067095 0.05989181 0.941348463     5983 1316  380
220 0.050    0.20 0.06495360 0.06272540 0.749652707     5967 1310  396
221 0.050    0.21 0.06923626 0.06555899 0.579127279     5951 1304  412
222 0.050    0.22 0.07066381 0.06890778 0.819348883     5927 1302  436
223 0.050    0.23 0.07351892 0.07122617 0.755654395     5913 1298  450
224 0.050    0.24 0.07637402 0.07444616 0.804564839     5892 1294  471
225 0.050    0.25 0.07922912 0.07766615 0.852197694     5871 1290  492
226 0.050    0.26 0.07994290 0.08088614 0.929150280     5847 1289  516
227 0.050    0.27 0.08279800 0.08397733 0.902421287     5827 1285  536
228 0.050    0.28 0.09207709 0.08925811 0.721064560     5799 1272  564
229 0.050    0.29 0.09778729 0.09312210 0.539898714     5777 1264  586
230 0.050    0.30 0.10135617 0.09763009 0.638837615     5747 1259  616
231 0.050    0.31 0.10492505 0.10110768 0.635076215     5725 1254  638
232 0.050    0.32 0.10920771 0.10432767 0.540680799     5706 1248  657
233 0.050    0.33 0.11491792 0.11038125 0.581300301     5667 1240  696
234 0.050    0.34 0.12062812 0.11591963 0.574098621     5632 1232  731
235 0.050    0.35 0.12562455 0.12313241 0.788179231     5583 1225  780
236 0.050    0.36 0.13133476 0.12995878 0.900281689     5538 1217  825
237 0.050    0.37 0.14061385 0.13691396 0.687622748     5497 1204  866
238 0.050    0.38 0.14632405 0.14502834 0.912223767     5442 1196  921
239 0.050    0.39 0.15631692 0.15262751 0.701621097     5397 1182  966
240 0.050    0.40 0.16345468 0.15984029 0.713224802     5351 1172 1012
241 0.050    0.41 0.17416131 0.16834106 0.546041101     5300 1157 1063
242 0.050    0.42 0.18772305 0.17851623 0.339322599     5240 1138 1123
243 0.050    0.43 0.19414704 0.18572901 0.391420467     5193 1129 1170
244 0.050    0.44 0.20271235 0.19448738 0.411134974     5137 1117 1226
245 0.050    0.45 0.21413276 0.20672334 0.471487652     5058 1101 1305
246 0.050    0.46 0.22341185 0.21612571 0.486397133     4998 1088 1365
247 0.050    0.47 0.23911492 0.22784647 0.282112946     4929 1066 1434
248 0.050    0.48 0.24910778 0.23647604 0.232329793     4876 1052 1487
249 0.050    0.49 0.25910064 0.24742401 0.278096796     4805 1038 1558
250 0.050    0.50 0.28051392 0.26146316 0.078596187     4726 1008 1637
251 0.050    0.51 0.29550321 0.27472952 0.058610152     4644  987 1719
252 0.050    0.52 0.31049251 0.28619268 0.028508021     4576  966 1787
253 0.050    0.53 0.32476802 0.29933024 0.023553135     4494  946 1869
254 0.050    0.54 0.33333333 0.31259660 0.069102579     4403  934 1960
255 0.050    0.55 0.34832263 0.32599176 0.052596035     4320  913 2043
256 0.050    0.56 0.36259814 0.33977331 0.049839302     4233  893 2130
257 0.050    0.57 0.37615989 0.35561566 0.081228801     4129  874 2234
258 0.050    0.58 0.39400428 0.37107161 0.053339144     4034  849 2329
259 0.050    0.59 0.40471092 0.38588357 0.116704922     3934  834 2429
260 0.050    0.60 0.42612420 0.40211231 0.046079285     3838  804 2525
261 0.050    0.61 0.43968594 0.41666667 0.057358463     3744  785 2619
262 0.050    0.62 0.45681656 0.43611540 0.089847986     3617  761 2746
263 0.050    0.63 0.47822984 0.45749614 0.090815710     3481  731 2882
264 0.050    0.64 0.49393291 0.47707367 0.171926306     3351  709 3012
265 0.050    0.65 0.50892220 0.49497682 0.261136207     3233  688 3130
266 0.050    0.66 0.52248394 0.51481195 0.545071269     3098  669 3265
267 0.050    0.67 0.53818701 0.53310149 0.695149108     2978  647 3385
268 0.050    0.68 0.56459672 0.55074704 0.262062098     2878  610 3485
269 0.050    0.69 0.58172734 0.56826378 0.273931093     2766  586 3597
270 0.050    0.70 0.60528194 0.58990211 0.206642750     2631  553 3732
271 0.050    0.71 0.62740899 0.60754766 0.098634693     2525  522 3838
272 0.050    0.72 0.64525339 0.63060278 0.220771520     2371  497 3992
273 0.050    0.73 0.67023555 0.65236991 0.128478716     2237  462 4126
274 0.050    0.74 0.68593862 0.67014426 0.174601518     2121  440 4242
275 0.050    0.75 0.70378301 0.68920659 0.203978629     1998  415 4365
276 0.050    0.76 0.72947894 0.70955693 0.074761483     1876  379 4487
277 0.050    0.77 0.74518201 0.72964967 0.157741911     1742  357 4621
278 0.050    0.78 0.76302641 0.75115920 0.271002182     1600  332 4763
279 0.050    0.79 0.77872948 0.76944874 0.381023910     1480  310 4883
280 0.050    0.80 0.79514632 0.78696548 0.429498811     1367  287 4996
281 0.050    0.81 0.80371163 0.80667182 0.785193247     1226  275 5137
282 0.050    0.82 0.82655246 0.82457496 0.860154833     1119  243 5244
283 0.050    0.83 0.84296931 0.84067491 0.826738587     1017  220 5346
284 0.050    0.84 0.86224126 0.85806285 0.650728551      909  193 5454
285 0.050    0.85 0.87508922 0.87287481 0.817660644      812  175 5551
286 0.050    0.86 0.89293362 0.88794436 0.543724848      720  150 5643
287 0.050    0.87 0.91006424 0.90056672 0.206610092      646  126 5717
288 0.050    0.88 0.92148465 0.91228748 0.196318015      571  110 5792
289 0.050    0.89 0.93219129 0.92490984 0.277310565      488   95 5875
290 0.050    0.90 0.94289793 0.93495621 0.203486271      425   80 5938
291 0.050    0.91 0.95503212 0.94345698 0.044622773      376   63 5987
292 0.050    0.92 0.96145610 0.95337455 0.129812489      308   54 6055
293 0.050    0.93 0.97002141 0.96161772 0.083316367      256   42 6107
294 0.050    0.94 0.97573162 0.96831530 0.095642845      212   34 6151
295 0.050    0.95 0.98286938 0.97514168 0.050302131      169   24 6194
296 0.050    0.96 0.98715203 0.98261206 0.185781546      117   18 6246
297 0.050    0.97 0.99000714 0.98737764 0.399970625       84   14 6279
298 0.050    0.98 0.99286224 0.99149923 0.650466342       56   10 6307
299 0.050    0.99 0.99643112 0.99600721 0.964951799       26    5 6337
300 0.050    1.00 1.00000000 1.00000000 0.000000000        0    0 6363
301 0.075    0.01 0.01925255 0.02099433 0.626642746     5869 1732  129
302 0.075    0.02 0.02604757 0.02743431 0.746669356     5831 1720  167
303 0.075    0.03 0.02774632 0.02910871 0.758882892     5821 1717  177
304 0.075    0.04 0.03114383 0.03232870 0.807417926     5802 1711  196
305 0.075    0.05 0.03340883 0.03464709 0.802818314     5788 1707  210
306 0.075    0.06 0.03680634 0.03735188 0.947246282     5773 1701  225
307 0.075    0.07 0.03737259 0.03915507 0.711688874     5760 1700  238
308 0.075    0.08 0.03963760 0.04070067 0.850311233     5752 1696  246
309 0.075    0.09 0.04303511 0.04211747 0.879944521     5747 1690  251
310 0.075    0.10 0.04473386 0.04314786 0.759167652     5742 1687  256
311 0.075    0.11 0.04699887 0.04456466 0.618187287     5735 1683  263
312 0.075    0.12 0.04869762 0.04662545 0.684957621     5722 1680  276
313 0.075    0.13 0.04926387 0.04752705 0.743915481     5716 1679  282
314 0.075    0.14 0.04983012 0.04829985 0.780920437     5711 1678  287
315 0.075    0.15 0.05096263 0.05010304 0.899464077     5699 1676  299
316 0.075    0.16 0.05436014 0.05280783 0.786141179     5684 1670  314
317 0.075    0.17 0.05775764 0.05577022 0.722521110     5667 1664  331
318 0.075    0.18 0.05945640 0.05692942 0.643358077     5661 1661  337
319 0.075    0.19 0.06172140 0.05989181 0.755341060     5642 1657  356
320 0.075    0.20 0.06511891 0.06272540 0.677305775     5626 1651  372
321 0.075    0.21 0.06964892 0.06555899 0.462116355     5612 1643  386
322 0.075    0.22 0.07078143 0.06890778 0.764007032     5588 1641  410
323 0.075    0.23 0.07361268 0.07122617 0.695795660     5575 1636  423
324 0.075    0.24 0.07701019 0.07444616 0.677811582     5556 1630  442
325 0.075    0.25 0.07927520 0.07766615 0.812765045     5535 1626  463
326 0.075    0.26 0.08040770 0.08088614 0.972678617     5512 1624  486
327 0.075    0.27 0.08380521 0.08397733 1.000000000     5494 1618  504
328 0.075    0.28 0.09229898 0.08925811 0.643757114     5468 1603  530
329 0.075    0.29 0.09739524 0.09312210 0.511527776     5447 1594  551
330 0.075    0.30 0.10135900 0.09763009 0.578853947     5419 1587  579
331 0.075    0.31 0.10475651 0.10110768 0.593490910     5398 1581  600
332 0.075    0.32 0.10815402 0.10432767 0.579447917     5379 1575  619
333 0.075    0.33 0.11325028 0.11038125 0.693177209     5341 1566  657
334 0.075    0.34 0.11834655 0.11591963 0.748832565     5307 1557  691
335 0.075    0.35 0.12400906 0.12313241 0.931178581     5261 1547  737
336 0.075    0.36 0.12967157 0.12995878 0.999536645     5218 1537  780
337 0.075    0.37 0.13929785 0.13691396 0.770143828     5181 1520  817
338 0.075    0.38 0.14552661 0.14502834 0.976694594     5129 1509  869
339 0.075    0.39 0.15458664 0.15262751 0.823675235     5086 1493  912
340 0.075    0.40 0.16194790 0.15984029 0.811848995     5043 1480  955
341 0.075    0.41 0.17157418 0.16834106 0.706207989     4994 1463 1004
342 0.075    0.42 0.18516421 0.17851623 0.426807118     4939 1439 1059
343 0.075    0.43 0.19195923 0.18572901 0.464678096     4895 1427 1103
344 0.075    0.44 0.20101925 0.19448738 0.450354184     4843 1411 1155
345 0.075    0.45 0.21404304 0.20672334 0.406094870     4771 1388 1227
346 0.075    0.46 0.22366931 0.21612571 0.399015740     4715 1371 1283
347 0.075    0.47 0.24009060 0.22784647 0.172750319     4653 1342 1345
348 0.075    0.48 0.24971687 0.23647604 0.144840036     4603 1325 1395
349 0.075    0.49 0.25934315 0.24742401 0.197305107     4535 1308 1463
350 0.075    0.50 0.28086070 0.26146316 0.037551378     4464 1270 1534
351 0.075    0.51 0.29558324 0.27472952 0.027571688     4387 1244 1611
352 0.075    0.52 0.31030578 0.28619268 0.011708809     4324 1218 1674
353 0.075    0.53 0.32559456 0.29933024 0.006678748     4249 1191 1749
354 0.075    0.54 0.33691959 0.31259660 0.013155648     4166 1171 1832
355 0.075    0.55 0.35107588 0.32599176 0.011416188     4087 1146 1911
356 0.075    0.56 0.36353341 0.33977331 0.017791389     4002 1124 1996
357 0.075    0.57 0.37655719 0.35561566 0.039081276     3902 1101 2096
358 0.075    0.58 0.39354473 0.37107161 0.028080979     3812 1071 2186
359 0.075    0.59 0.40430351 0.38588357 0.074859803     3716 1052 2282
360 0.075    0.60 0.42412231 0.40211231 0.034124444     3625 1017 2373
361 0.075    0.61 0.43544734 0.41666667 0.072830452     3532  997 2466
362 0.075    0.62 0.45130238 0.43611540 0.150736138     3409  969 2589
363 0.075    0.63 0.47734994 0.45749614 0.060351524     3289  923 2709
364 0.075    0.64 0.49433749 0.47707367 0.104063889     3167  893 2831
365 0.075    0.65 0.50849377 0.49497682 0.205681522     3053  868 2945
366 0.075    0.66 0.52095130 0.51481195 0.575316542     2921  846 3077
367 0.075    0.67 0.53963760 0.53310149 0.549008357     2812  813 3186
368 0.075    0.68 0.56398641 0.55074704 0.213001960     2718  770 3280
369 0.075    0.69 0.58210646 0.56826378 0.190579052     2614  738 3384
370 0.075    0.70 0.60475651 0.58990211 0.156646263     2486  698 3512
371 0.075    0.71 0.62457531 0.60754766 0.101099130     2384  663 3614
372 0.075    0.72 0.64552661 0.63060278 0.146961564     2242  626 3756
373 0.075    0.73 0.66817667 0.65236991 0.119101352     2113  586 3885
374 0.075    0.74 0.68459796 0.67014426 0.149573097     2004  557 3994
375 0.075    0.75 0.70045300 0.68920659 0.257395136     1884  529 4114
376 0.075    0.76 0.72310306 0.70955693 0.162455942     1766  489 4232
377 0.075    0.77 0.74065685 0.72964967 0.248317499     1641  458 4357
378 0.075    0.78 0.76104190 0.75115920 0.288417935     1510  422 4488
379 0.075    0.79 0.77916195 0.76944874 0.284405183     1400  390 4598
380 0.075    0.80 0.79445074 0.78696548 0.400351261     1291  363 4707
381 0.075    0.81 0.80407701 0.80667182 0.779571933     1155  346 4843
382 0.075    0.82 0.82672707 0.82457496 0.814246211     1056  306 4942
383 0.075    0.83 0.84258211 0.84067491 0.831974501      959  278 5039
384 0.075    0.84 0.86013590 0.85806285 0.806283846      855  247 5143
385 0.075    0.85 0.87259343 0.87287481 1.000000000      762  225 5236
386 0.075    0.86 0.89014723 0.88794436 0.771064227      676  194 5322
387 0.075    0.87 0.90600227 0.90056672 0.410375906      606  166 5392
388 0.075    0.88 0.92015855 0.91228748 0.199662154      540  141 5458
389 0.075    0.89 0.93091733 0.92490984 0.299021531      461  122 5537
390 0.075    0.90 0.94280861 0.93495621 0.142228708      404  101 5594
391 0.075    0.91 0.95469989 0.94345698 0.023283682      359   80 5639
392 0.075    0.92 0.96092865 0.95337455 0.099175856      293   69 5705
393 0.075    0.93 0.96885617 0.96161772 0.083459899      243   55 5755
394 0.075    0.94 0.97451869 0.96831530 0.106093461      201   45 5797
395 0.075    0.95 0.98187995 0.97514168 0.047444627      161   32 5837
396 0.075    0.96 0.98584371 0.98261206 0.280804480      110   25 5888
397 0.075    0.97 0.98980747 0.98737764 0.357895772       80   18 5918
398 0.075    0.98 0.99263873 0.99149923 0.655604309       53   13 5945
399 0.075    0.99 0.99660249 0.99600721 0.812917085       25    6 5973
400 0.075    1.00 1.00000000 1.00000000 0.000000000        0    0 5998
401 0.100    0.01 0.01823417 0.02099433 0.348118259     5555 2046  125
402 0.100    0.02 0.02591171 0.02743431 0.675134692     5521 2030  159
403 0.100    0.03 0.02735125 0.02910871 0.629953619     5511 2027  169
404 0.100    0.04 0.03119002 0.03232870 0.786232104     5494 2019  186
405 0.100    0.05 0.03310940 0.03464709 0.704884485     5480 2015  200
406 0.100    0.06 0.03694818 0.03735188 0.963231465     5467 2007  213
407 0.100    0.07 0.03790787 0.03915507 0.781648778     5455 2005  225
408 0.100    0.08 0.03982726 0.04070067 0.864135774     5447 2001  233
409 0.100    0.09 0.04318618 0.04211747 0.825692322     5443 1994  237
410 0.100    0.10 0.04510557 0.04314786 0.651834839     5439 1990  241
411 0.100    0.11 0.04750480 0.04456466 0.484910901     5433 1985  247
412 0.100    0.12 0.04942418 0.04662545 0.517142017     5421 1981  259
413 0.100    0.13 0.04990403 0.04752705 0.591896667     5415 1980  265
414 0.100    0.14 0.05038388 0.04829985 0.646182330     5410 1979  270
415 0.100    0.15 0.05230326 0.05010304 0.631519272     5400 1975  280
416 0.100    0.16 0.05518234 0.05280783 0.610468390     5385 1969  295
417 0.100    0.17 0.05854127 0.05577022 0.556065748     5369 1962  311
418 0.100    0.18 0.05998081 0.05692942 0.517240959     5363 1959  317
419 0.100    0.19 0.06238004 0.05989181 0.613061182     5345 1954  335
420 0.100    0.20 0.06525912 0.06272540 0.613619714     5329 1948  351
421 0.100    0.21 0.07005758 0.06555899 0.358445676     5317 1938  363
422 0.100    0.22 0.07149712 0.06890778 0.620566243     5294 1935  386
423 0.100    0.23 0.07437620 0.07122617 0.545922893     5282 1929  398
424 0.100    0.24 0.07821497 0.07444616 0.473054220     5265 1921  415
425 0.100    0.25 0.08061420 0.07766615 0.589168703     5245 1916  435
426 0.100    0.26 0.08253359 0.08088614 0.782917405     5224 1912  456
427 0.100    0.27 0.08589251 0.08397733 0.747166290     5207 1905  473
428 0.100    0.28 0.09404990 0.08925811 0.394164158     5183 1888  497
429 0.100    0.29 0.09932821 0.09312210 0.273185721     5164 1877  516
430 0.100    0.30 0.10316699 0.09763009 0.340847567     5137 1869  543
431 0.100    0.31 0.10604607 0.10110768 0.405512453     5116 1863  564
432 0.100    0.32 0.11036468 0.10432767 0.311456774     5100 1854  580
433 0.100    0.33 0.11468330 0.11038125 0.489021671     5062 1845  618
434 0.100    0.34 0.11996161 0.11591963 0.526154371     5030 1834  650
435 0.100    0.35 0.12619962 0.12313241 0.646066054     4987 1821  693
436 0.100    0.36 0.13195777 0.12995878 0.780085681     4946 1809  734
437 0.100    0.37 0.14011516 0.13691396 0.645677446     4909 1792  771
438 0.100    0.38 0.14731286 0.14502834 0.756635863     4861 1777  819
439 0.100    0.39 0.15642994 0.15262751 0.597004835     4821 1758  859
440 0.100    0.40 0.16314779 0.15984029 0.655037099     4779 1744  901
441 0.100    0.41 0.17274472 0.16834106 0.552560912     4733 1724  947
442 0.100    0.42 0.18570058 0.17851623 0.333111194     4681 1697  999
443 0.100    0.43 0.19193858 0.18572901 0.412616270     4638 1684 1042
444 0.100    0.44 0.20009597 0.19448738 0.469103005     4587 1667 1093
445 0.100    0.45 0.21257198 0.20672334 0.459773374     4518 1641 1162
446 0.100    0.46 0.22168906 0.21612571 0.490011016     4464 1622 1216
447 0.100    0.47 0.23656430 0.22784647 0.280685652     4404 1591 1276
448 0.100    0.48 0.24568138 0.23647604 0.260116604     4356 1572 1324
449 0.100    0.49 0.25383877 0.24742401 0.445020590     4288 1555 1392
450 0.100    0.50 0.27351248 0.26146316 0.151473893     4220 1514 1460
451 0.100    0.51 0.28646833 0.27472952 0.169162993     4144 1487 1536
452 0.100    0.52 0.30182342 0.28619268 0.069150369     4087 1455 1593
453 0.100    0.53 0.31573896 0.29933024 0.059516689     4014 1426 1666
454 0.100    0.54 0.32869482 0.31259660 0.067865968     3938 1399 1742
455 0.100    0.55 0.34357006 0.32599176 0.048359602     3865 1368 1815
456 0.100    0.56 0.35700576 0.33977331 0.055511990     3786 1340 1894
457 0.100    0.57 0.37044146 0.35561566 0.103896756     3691 1312 1989
458 0.100    0.58 0.38867562 0.37107161 0.055059863     3609 1274 2071
459 0.100    0.59 0.39827255 0.38588357 0.182857608     3514 1254 2166
460 0.100    0.60 0.41746641 0.40211231 0.099928818     3428 1214 2252
461 0.100    0.61 0.42850288 0.41666667 0.209331922     3338 1191 2342
462 0.100    0.62 0.44529750 0.43611540 0.335838389     3222 1156 2458
463 0.100    0.63 0.47072937 0.45749614 0.163919684     3109 1103 2571
464 0.100    0.64 0.48656430 0.47707367 0.322905015     2990 1070 2690
465 0.100    0.65 0.50383877 0.49497682 0.357361110     2887 1034 2793
466 0.100    0.66 0.51919386 0.51481195 0.658250483     2765 1002 2915
467 0.100    0.67 0.53742802 0.53310149 0.661978101     2661  964 3019
468 0.100    0.68 0.56046065 0.55074704 0.309382702     2572  916 3108
469 0.100    0.69 0.57821497 0.56826378 0.295363760     2473  879 3207
470 0.100    0.70 0.60028791 0.58990211 0.270912341     2351  833 3329
471 0.100    0.71 0.61948177 0.60754766 0.201173701     2254  793 3426
472 0.100    0.72 0.64059501 0.63060278 0.280833060     2119  749 3561
473 0.100    0.73 0.66410749 0.65236991 0.197534327     1999  700 3681
474 0.100    0.74 0.68042226 0.67014426 0.254486066     1895  666 3785
475 0.100    0.75 0.69721689 0.68920659 0.370207927     1782  631 3898
476 0.100    0.76 0.71976967 0.70955693 0.240998002     1671  584 4009
477 0.100    0.77 0.73800384 0.72964967 0.329515053     1553  546 4127
478 0.100    0.78 0.75767754 0.75115920 0.438297926     1427  505 4253
479 0.100    0.79 0.77591171 0.76944874 0.430356254     1323  467 4357
480 0.100    0.80 0.79366603 0.78696548 0.399704543     1224  430 4456
481 0.100    0.81 0.80566219 0.80667182 0.917147737     1096  405 4584
482 0.100    0.82 0.82629559 0.82457496 0.835393215     1000  362 4680
483 0.100    0.83 0.84309021 0.84067491 0.751056996      910  327 4770
484 0.100    0.84 0.86180422 0.85806285 0.592306093      814  288 4866
485 0.100    0.85 0.87523992 0.87287481 0.733475913      727  260 4953
486 0.100    0.86 0.89155470 0.88794436 0.568484522      644  226 5036
487 0.100    0.87 0.90738964 0.90056672 0.240341998      579  193 5101
488 0.100    0.88 0.92082534 0.91228748 0.117433963      516  165 5164
489 0.100    0.89 0.93042226 0.92490984 0.285607385      438  145 5242
490 0.100    0.90 0.94193858 0.93495621 0.144490012      384  121 5296
491 0.100    0.91 0.95393474 0.94345698 0.017991934      343   96 5337
492 0.100    0.92 0.96113244 0.95337455 0.057020149      281   81 5399
493 0.100    0.93 0.96880998 0.96161772 0.053428493      233   65 5447
494 0.100    0.94 0.97408829 0.96831530 0.091801307      192   54 5488
495 0.100    0.95 0.98080614 0.97514168 0.062947583      153   40 5527
496 0.100    0.96 0.98656430 0.98261206 0.129564763      107   28 5573
497 0.100    0.97 0.99088292 0.98737764 0.118495866       79   19 5601
498 0.100    0.98 0.99328215 0.99149923 0.369702010       52   14 5628
499 0.100    0.99 0.99712092 0.99600721 0.459588261       25    6 5655
500 0.100    1.00 1.00000000 1.00000000 0.000000000        0    0 5680
    Dboth
1      11
2      13
3      15
4      17
5      18
6      21
7      22
8      25
9      28
10     28
11     30
12     30
13     31
14     31
15     32
16     35
17     37
18     37
19     37
20     38
21     39
22     40
23     42
24     45
25     46
26     46
27     46
28     51
29     54
30     55
31     56
32     58
33     60
34     61
35     65
36     68
37     75
38     77
39     81
40     86
41     90
42     98
43    101
44    105
45    111
46    114
47    122
48    127
49    134
50    142
51    150
52    156
53    163
54    168
55    174
56    182
57    191
58    202
59    206
60    216
61    224
62    230
63    243
64    249
65    255
66    262
67    271
68    282
69    289
70    303
71    315
72    320
73    328
74    332
75    340
76    355
77    359
78    372
79    381
80    388
81    394
82    400
83    410
84    418
85    421
86    431
87    439
88    444
89    445
90    450
91    451
92    454
93    458
94    460
95    465
96    467
97    467
98    467
99    469
100   470
101    16
102    22
103    25
104    28
105    30
106    35
107    36
108    39
109    43
110    43
111    46
112    47
113    48
114    48
115    49
116    52
117    54
118    56
119    57
120    62
121    67
122    69
123    73
124    76
125    77
126    78
127    80
128    87
129    92
130    96
131    99
132   103
133   108
134   114
135   119
136   122
137   132
138   139
139   150
140   157
141   165
142   178
143   184
144   190
145   200
146   206
147   221
148   230
149   242
150   259
151   277
152   289
153   305
154   316
155   326
156   341
157   358
158   375
159   383
160   403
161   416
162   433
163   450
164   462
165   477
166   491
167   503
168   524
169   540
170   562
171   585
172   599
173   620
174   631
175   648
176   672
177   683
178   704
179   722
180   735
181   742
182   767
183   780
184   800
185   813
186   833
187   849
188   860
189   867
190   876
191   885
192   891
193   897
194   902
195   909
196   914
197   916
198   917
199   920
200   923
201    27
202    36
203    39
204    43
205    46
206    51
207    52
208    56
209    60
210    62
211    66
212    69
213    70
214    70
215    71
216    76
217    81
218    84
219    85
220    91
221    97
222    99
223   103
224   107
225   111
226   112
227   116
228   129
229   137
230   142
231   147
232   153
233   161
234   169
235   176
236   184
237   197
238   205
239   219
240   229
241   244
242   263
243   272
244   284
245   300
246   313
247   335
248   349
249   363
250   393
251   414
252   435
253   455
254   467
255   488
256   508
257   527
258   552
259   567
260   597
261   616
262   640
263   670
264   692
265   713
266   732
267   754
268   791
269   815
270   848
271   879
272   904
273   939
274   961
275   986
276  1022
277  1044
278  1069
279  1091
280  1114
281  1126
282  1158
283  1181
284  1208
285  1226
286  1251
287  1275
288  1291
289  1306
290  1321
291  1338
292  1347
293  1359
294  1367
295  1377
296  1383
297  1387
298  1391
299  1396
300  1401
301    34
302    46
303    49
304    55
305    59
306    65
307    66
308    70
309    76
310    79
311    83
312    86
313    87
314    88
315    90
316    96
317   102
318   105
319   109
320   115
321   123
322   125
323   130
324   136
325   140
326   142
327   148
328   163
329   172
330   179
331   185
332   191
333   200
334   209
335   219
336   229
337   246
338   257
339   273
340   286
341   303
342   327
343   339
344   355
345   378
346   395
347   424
348   441
349   458
350   496
351   522
352   548
353   575
354   595
355   620
356   642
357   665
358   695
359   714
360   749
361   769
362   797
363   843
364   873
365   898
366   920
367   953
368   996
369  1028
370  1068
371  1103
372  1140
373  1180
374  1209
375  1237
376  1277
377  1308
378  1344
379  1376
380  1403
381  1420
382  1460
383  1488
384  1519
385  1541
386  1572
387  1600
388  1625
389  1644
390  1665
391  1686
392  1697
393  1711
394  1721
395  1734
396  1741
397  1748
398  1753
399  1760
400  1766
401    38
402    54
403    57
404    65
405    69
406    77
407    79
408    83
409    90
410    94
411    99
412   103
413   104
414   105
415   109
416   115
417   122
418   125
419   130
420   136
421   146
422   149
423   155
424   163
425   168
426   172
427   179
428   196
429   207
430   215
431   221
432   230
433   239
434   250
435   263
436   275
437   292
438   307
439   326
440   340
441   360
442   387
443   400
444   417
445   443
446   462
447   493
448   512
449   529
450   570
451   597
452   629
453   658
454   685
455   716
456   744
457   772
458   810
459   830
460   870
461   893
462   928
463   981
464  1014
465  1050
466  1082
467  1120
468  1168
469  1205
470  1251
471  1291
472  1335
473  1384
474  1418
475  1453
476  1500
477  1538
478  1579
479  1617
480  1654
481  1679
482  1722
483  1757
484  1796
485  1824
486  1858
487  1891
488  1919
489  1939
490  1963
491  1988
492  2003
493  2019
494  2030
495  2044
496  2056
497  2065
498  2070
499  2078
500  2084
enrichment.plotter(gene.hic.filt, "median_FDR.C", "adj.P.Val", "Median FDR of Hi-C Contacts Overlapping Gene, Chimp")
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs   prop.exp     chisq.p Dneither   DE DHiC
1   0.010    0.01 0.02407002 0.02082530 0.740000502     7171  446  151
2   0.010    0.02 0.02625821 0.02686721 1.000000000     7125  445  197
3   0.010    0.03 0.03063457 0.02879547 0.921802892     7112  443  210
4   0.010    0.04 0.03282276 0.03226636 1.000000000     7086  442  236
5   0.010    0.05 0.03501094 0.03432318 1.000000000     7071  441  251
6   0.010    0.06 0.03719912 0.03689420 1.000000000     7052  440  270
7   0.010    0.07 0.03938731 0.03817971 0.989587066     7043  439  279
8   0.010    0.08 0.04376368 0.03959378 0.728174656     7034  437  288
9   0.010    0.09 0.04814004 0.04062219 0.473375066     7028  435  294
10  0.010    0.10 0.04814004 0.04139350 0.531804704     7022  435  300
11  0.010    0.11 0.05251641 0.04280756 0.348371342     7013  433  309
12  0.010    0.12 0.05251641 0.04486438 0.485143162     6997  433  325
13  0.010    0.13 0.05251641 0.04537858 0.522278372     6993  433  329
14  0.010    0.14 0.05251641 0.04679265 0.629075382     6982  433  340
15  0.010    0.15 0.05470460 0.04859236 0.607072083     6969  432  353
16  0.010    0.16 0.05908096 0.05077773 0.469342894     6954  430  368
17  0.010    0.17 0.06345733 0.05360586 0.391601740     6934  428  388
18  0.010    0.18 0.06345733 0.05489137 0.469779205     6924  428  398
19  0.010    0.19 0.06564551 0.05810515 0.543743114     6900  427  422
20  0.010    0.20 0.06564551 0.06016197 0.684191681     6884  427  438
21  0.010    0.21 0.07002188 0.06260445 0.565183912     6867  425  455
22  0.010    0.22 0.07002188 0.06556113 0.764395742     6844  425  478
23  0.010    0.23 0.07221007 0.06800360 0.785306384     6826  424  496
24  0.010    0.24 0.07877462 0.07108883 0.571926775     6805  421  517
25  0.010    0.25 0.08315098 0.07391696 0.493006856     6785  419  537
26  0.010    0.26 0.08315098 0.07751639 0.708300929     6757  419  565
27  0.010    0.27 0.08533917 0.08034452 0.751862070     6736  418  586
28  0.010    0.28 0.09628009 0.08432961 0.389316878     6710  413  612
29  0.010    0.29 0.10284464 0.08780049 0.277414887     6686  410  636
30  0.010    0.30 0.10284464 0.09307109 0.510364986     6645  410  677
31  0.010    0.31 0.10503282 0.09615632 0.560782547     6622  409  700
32  0.010    0.32 0.10722101 0.10091271 0.702881487     6586  408  736
33  0.010    0.33 0.10940919 0.10618331 0.878813027     6546  407  776
34  0.010    0.34 0.11159737 0.11158247 1.000000000     6505  406  817
35  0.010    0.35 0.11816193 0.11801003 1.000000000     6458  403  864
36  0.010    0.36 0.12035011 0.12379483 0.875035053     6414  402  908
37  0.010    0.37 0.13129103 0.13086515 1.000000000     6364  397  958
38  0.010    0.38 0.13785558 0.13934953 0.979702663     6301  394 1021
39  0.010    0.39 0.14660832 0.14680550 1.000000000     6247  390 1075
40  0.010    0.40 0.15536105 0.15323306 0.949571737     6201  386 1121
41  0.010    0.41 0.16630197 0.16171744 0.834536687     6140  381 1182
42  0.010    0.42 0.18380744 0.17084458 0.487148241     6077  373 1245
43  0.010    0.43 0.18599562 0.17714359 0.654340184     6029  372 1293
44  0.010    0.44 0.19256018 0.18549942 0.735185510     5967  369 1355
45  0.010    0.45 0.20568928 0.19732613 0.687346692     5881  363 1441
46  0.010    0.46 0.21006565 0.20606762 0.874302361     5815  361 1507
47  0.010    0.47 0.22100656 0.21827998 0.930607262     5725  356 1597
48  0.010    0.48 0.23632385 0.22663581 0.651041771     5667  349 1655
49  0.010    0.49 0.25164114 0.23679136 0.475852628     5595  342 1727
50  0.010    0.50 0.26477024 0.25118910 0.525805204     5489  336 1833
51  0.010    0.51 0.28227571 0.26442988 0.402622477     5394  328 1928
52  0.010    0.52 0.29759300 0.27612804 0.315384371     5310  321 2012
53  0.010    0.53 0.30853392 0.28936881 0.379894264     5212  316 2110
54  0.010    0.54 0.32166302 0.30273814 0.392466148     5114  310 2208
55  0.010    0.55 0.32822757 0.31572182 0.588517719     5016  307 2306
56  0.010    0.56 0.33698031 0.32767708 0.699955001     4927  303 2395
57  0.010    0.57 0.35667396 0.34323178 0.566599573     4815  294 2507
58  0.010    0.58 0.37855580 0.35801517 0.371435554     4710  284 2612
59  0.010    0.59 0.38949672 0.37189870 0.451793486     4607  279 2715
60  0.010    0.60 0.41794311 0.38925312 0.212359048     4485  266 2837
61  0.010    0.61 0.42888403 0.40532202 0.313269156     4365  261 2957
62  0.010    0.62 0.44638950 0.42383340 0.338576271     4229  253 3093
63  0.010    0.63 0.47483589 0.44453015 0.195206499     4081  240 3241
64  0.010    0.64 0.49234136 0.46227021 0.200317833     3951  232 3371
65  0.010    0.65 0.51203501 0.47923898 0.162027506     3828  223 3494
66  0.010    0.66 0.52954048 0.49903587 0.194940856     3682  215 3640
67  0.010    0.67 0.55798687 0.51831855 0.088928478     3545  202 3777
68  0.010    0.68 0.57768053 0.53708703 0.080895211     3408  193 3914
69  0.010    0.69 0.60175055 0.55636971 0.049506477     3269  182 4053
70  0.010    0.70 0.63238512 0.57950893 0.020810427     3103  168 4219
71  0.010    0.71 0.65864333 0.59802031 0.007466153     2971  156 4351
72  0.010    0.72 0.67177243 0.62077388 0.023429435     2800  150 4522
73  0.010    0.73 0.69146608 0.64237048 0.027332457     2641  141 4681
74  0.010    0.74 0.69803063 0.65959635 0.082496181     2510  138 4812
75  0.010    0.75 0.71115974 0.67900758 0.142684344     2365  132 4957
76  0.010    0.76 0.74179431 0.69983288 0.049445580     2217  118 5105
77  0.010    0.77 0.75273523 0.72142949 0.137554174     2054  113 5268
78  0.010    0.78 0.78774617 0.74302610 0.027813680     1902   97 5420
79  0.010    0.79 0.80087527 0.76179458 0.049425600     1762   91 5560
80  0.010    0.80 0.81619256 0.77902044 0.055364007     1635   84 5687
81  0.010    0.81 0.82275711 0.79778892 0.190283215     1492   81 5830
82  0.010    0.82 0.83369803 0.81578609 0.339107493     1357   76 5965
83  0.010    0.83 0.85120350 0.83262630 0.302099516     1234   68 6088
84  0.010    0.84 0.87308534 0.84869521 0.152009817     1119   58 6203
85  0.010    0.85 0.88183807 0.86617817 0.345835289      987   54 6335
86  0.010    0.86 0.90371991 0.88301838 0.178865317      866   44 6456
87  0.010    0.87 0.92122538 0.89613061 0.083024256      772   36 6550
88  0.010    0.88 0.92341357 0.90821442 0.281721047      679   35 6643
89  0.010    0.89 0.93216630 0.92132665 0.425096043      581   31 6741
90  0.010    0.90 0.94310722 0.93148220 0.358352917      507   26 6815
91  0.010    0.91 0.94529540 0.94073788 0.746534116      436   25 6886
92  0.010    0.92 0.95842451 0.95192184 0.577476414      355   19 6967
93  0.010    0.93 0.96498906 0.96040622 0.693422120      292   16 7030
94  0.010    0.94 0.96498906 0.96747654 0.862584837      237   16 7085
95  0.010    0.95 0.98030635 0.97544672 0.591864006      182    9 7140
96  0.010    0.96 0.98687090 0.98225993 0.557173711      132    6 7190
97  0.010    0.97 0.98687090 0.98753053 1.000000000       91    6 7231
98  0.010    0.98 0.98687090 0.99138707 0.414491736       61    6 7261
99  0.010    0.99 0.99781182 0.99601491 0.805832349       30    1 7292
100 0.010    1.00 1.00000000 1.00000000 0.000000000        0    0 7322
101 0.025    0.01 0.01847826 0.02082530 0.683294327     6714  903  145
102 0.025    0.02 0.02500000 0.02686721 0.791440987     6673  897  186
103 0.025    0.03 0.02826087 0.02879547 1.000000000     6661  894  198
104 0.025    0.04 0.03043478 0.03226636 0.813850028     6636  892  223
105 0.025    0.05 0.03260870 0.03432318 0.835411830     6622  890  237
106 0.025    0.06 0.03695652 0.03689420 1.000000000     6606  886  253
107 0.025    0.07 0.03913043 0.03817971 0.945271488     6598  884  261
108 0.025    0.08 0.04130435 0.03959378 0.846703992     6589  882  270
109 0.025    0.09 0.04347826 0.04062219 0.705135216     6583  880  276
110 0.025    0.10 0.04347826 0.04139350 0.802639536     6577  880  282
111 0.025    0.11 0.04782609 0.04280756 0.475160888     6570  876  289
112 0.025    0.12 0.04891304 0.04486438 0.584408251     6555  875  304
113 0.025    0.13 0.04891304 0.04537858 0.642509832     6551  875  308
114 0.025    0.14 0.04891304 0.04679265 0.809410956     6540  875  319
115 0.025    0.15 0.05000000 0.04859236 0.896706602     6527  874  332
116 0.025    0.16 0.05217391 0.05077773 0.900160377     6512  872  347
117 0.025    0.17 0.05652174 0.05360586 0.733684301     6494  868  365
118 0.025    0.18 0.05869565 0.05489137 0.643764894     6486  866  373
119 0.025    0.19 0.06195652 0.05810515 0.647858934     6464  863  395
120 0.025    0.20 0.06521739 0.06016197 0.539931824     6451  860  408
121 0.025    0.21 0.06956522 0.06260445 0.392172922     6436  856  423
122 0.025    0.22 0.07065217 0.06556113 0.552859956     6414  855  445
123 0.025    0.23 0.07391304 0.06800360 0.491141678     6398  852  461
124 0.025    0.24 0.07826087 0.07108883 0.404723598     6378  848  481
125 0.025    0.25 0.08043478 0.07391696 0.460759584     6358  846  501
126 0.025    0.26 0.08260870 0.07751639 0.582678830     6332  844  527
127 0.025    0.27 0.08586957 0.08034452 0.553869579     6313  841  546
128 0.025    0.28 0.09239130 0.08432961 0.382151770     6288  835  571
129 0.025    0.29 0.09673913 0.08780049 0.337956338     6265  831  594
130 0.025    0.30 0.10000000 0.09307109 0.477741266     6227  828  632
131 0.025    0.31 0.10217391 0.09615632 0.548641931     6205  826  654
132 0.025    0.32 0.10652174 0.10091271 0.586976497     6172  822  687
133 0.025    0.33 0.11195652 0.10618331 0.583456452     6136  817  723
134 0.025    0.34 0.11630435 0.11158247 0.668158947     6098  813  761
135 0.025    0.35 0.12065217 0.11801003 0.833570012     6052  809  807
136 0.025    0.36 0.12173913 0.12379483 0.882093597     6008  808  851
137 0.025    0.37 0.13043478 0.13086515 1.000000000     5961  800  898
138 0.025    0.38 0.13695652 0.13934953 0.863034562     5901  794  958
139 0.025    0.39 0.15000000 0.14680550 0.808811332     5855  782 1004
140 0.025    0.40 0.15978261 0.15323306 0.590170558     5814  773 1045
141 0.025    0.41 0.16956522 0.16171744 0.521645409     5757  764 1102
142 0.025    0.42 0.18478261 0.17084458 0.250321575     5700  750 1159
143 0.025    0.43 0.18695652 0.17714359 0.432893254     5653  748 1206
144 0.025    0.44 0.19239130 0.18549942 0.597803787     5593  743 1266
145 0.025    0.45 0.20652174 0.19732613 0.482528673     5514  730 1345
146 0.025    0.46 0.21521739 0.20606762 0.491895041     5454  722 1405
147 0.025    0.47 0.22717391 0.21827998 0.513766423     5370  711 1489
148 0.025    0.48 0.23804348 0.22663581 0.401898206     5315  701 1544
149 0.025    0.49 0.25434783 0.23679136 0.196111089     5251  686 1608
150 0.025    0.50 0.27173913 0.25118910 0.136201745     5155  670 1704
151 0.025    0.51 0.28913043 0.26442988 0.076843090     5068  654 1791
152 0.025    0.52 0.30652174 0.27612804 0.031030162     4993  638 1866
153 0.025    0.53 0.31739130 0.28936881 0.050301017     4900  628 1959
154 0.025    0.54 0.33478261 0.30273814 0.026779556     4812  612 2047
155 0.025    0.55 0.34239130 0.31572182 0.069425538     4718  605 2141
156 0.025    0.56 0.35652174 0.32767708 0.051453066     4638  592 2221
157 0.025    0.57 0.37282609 0.34323178 0.048104702     4532  577 2327
158 0.025    0.58 0.39021739 0.35801517 0.032918632     4433  561 2426
159 0.025    0.59 0.40000000 0.37189870 0.065504029     4334  552 2525
160 0.025    0.60 0.42173913 0.38925312 0.034331370     4219  532 2640
161 0.025    0.61 0.43695652 0.40532202 0.040796362     4108  518 2751
162 0.025    0.62 0.45543478 0.42383340 0.042342328     3981  501 2878
163 0.025    0.63 0.47608696 0.44453015 0.043798783     3839  482 3020
164 0.025    0.64 0.49130435 0.46227021 0.064913111     3715  468 3144
165 0.025    0.65 0.50978261 0.47923898 0.052405836     3600  451 3259
166 0.025    0.66 0.52500000 0.49903587 0.100535319     3460  437 3399
167 0.025    0.67 0.54565217 0.51831855 0.083291848     3329  418 3530
168 0.025    0.68 0.56847826 0.53708703 0.045676048     3204  397 3655
169 0.025    0.69 0.59021739 0.55636971 0.030359381     3074  377 3785
170 0.025    0.70 0.61304348 0.57950893 0.030865347     2915  356 3944
171 0.025    0.71 0.63804348 0.59802031 0.009295449     2794  333 4065
172 0.025    0.72 0.65000000 0.62077388 0.056192483     2628  322 4231
173 0.025    0.73 0.67826087 0.64237048 0.017212336     2486  296 4373
174 0.025    0.74 0.68804348 0.65959635 0.057148434     2361  287 4498
175 0.025    0.75 0.70217391 0.67900758 0.117520662     2223  274 4636
176 0.025    0.76 0.72826087 0.69983288 0.049389577     2085  250 4774
177 0.025    0.77 0.74456522 0.72142949 0.103551946     1932  235 4927
178 0.025    0.78 0.77065217 0.74302610 0.045282187     1788  211 5071
179 0.025    0.79 0.78913043 0.76179458 0.042192390     1659  194 5200
180 0.025    0.80 0.80108696 0.77902044 0.093810404     1536  183 5323
181 0.025    0.81 0.80869565 0.79778892 0.404595792     1397  176 5462
182 0.025    0.82 0.82717391 0.81578609 0.366204115     1274  159 5585
183 0.025    0.83 0.84130435 0.83262630 0.481514981     1156  146 5703
184 0.025    0.84 0.85978261 0.84869521 0.341887842     1048  129 5811
185 0.025    0.85 0.87391304 0.86617817 0.495053280      925  116 5934
186 0.025    0.86 0.89565217 0.88301838 0.224320237      814   96 6045
187 0.025    0.87 0.90978261 0.89613061 0.165175759      725   83 6134
188 0.025    0.88 0.91630435 0.90821442 0.398513009      637   77 6222
189 0.025    0.89 0.92826087 0.92132665 0.443227755      546   66 6313
190 0.025    0.90 0.93804348 0.93148220 0.441632462      476   57 6383
191 0.025    0.91 0.94782609 0.94073788 0.370598868      413   48 6446
192 0.025    0.92 0.95978261 0.95192184 0.269227061      337   37 6522
193 0.025    0.93 0.96521739 0.96040622 0.479608953      276   32 6583
194 0.025    0.94 0.96739130 0.96747654 1.000000000      223   30 6636
195 0.025    0.95 0.97826087 0.97544672 0.635542235      171   20 6688
196 0.025    0.96 0.98478261 0.98225993 0.628165295      124   14 6735
197 0.025    0.97 0.98804348 0.98753053 1.000000000       86   11 6773
198 0.025    0.98 0.98913043 0.99138707 0.549266675       57   10 6802
199 0.025    0.99 0.99565217 0.99601491 1.000000000       27    4 6832
200 0.025    1.00 1.00000000 1.00000000 0.000000000        0    0 6859
201 0.050    0.01 0.02004295 0.02082530 0.902383225     6248 1369  134
202 0.050    0.02 0.02648533 0.02686721 0.995118995     6210 1360  172
203 0.050    0.03 0.02863278 0.02879547 1.000000000     6198 1357  184
204 0.050    0.04 0.03221188 0.03226636 1.000000000     6176 1352  206
205 0.050    0.05 0.03435934 0.03432318 1.000000000     6163 1349  219
206 0.050    0.06 0.03722262 0.03689420 1.000000000     6147 1345  235
207 0.050    0.07 0.03865426 0.03817971 0.979962636     6139 1343  243
208 0.050    0.08 0.04151754 0.03959378 0.740377927     6132 1339  250
209 0.050    0.09 0.04294918 0.04062219 0.680637505     6126 1337  256
210 0.050    0.10 0.04366500 0.04139350 0.691802563     6121 1336  261
211 0.050    0.11 0.04652827 0.04280756 0.493012315     6114 1332  268
212 0.050    0.12 0.04867573 0.04486438 0.491190866     6101 1329  281
213 0.050    0.13 0.04867573 0.04537858 0.560067497     6097 1329  285
214 0.050    0.14 0.04867573 0.04679265 0.765701496     6086 1329  296
215 0.050    0.15 0.04939155 0.04859236 0.932508475     6073 1328  309
216 0.050    0.16 0.05225483 0.05077773 0.833386489     6060 1324  322
217 0.050    0.17 0.05654975 0.05360586 0.635666460     6044 1318  338
218 0.050    0.18 0.05869721 0.05489137 0.532191590     6037 1315  345
219 0.050    0.19 0.06227631 0.05810515 0.501191342     6017 1310  365
220 0.050    0.20 0.06442377 0.06016197 0.498107176     6004 1307  378
221 0.050    0.21 0.06800286 0.06260445 0.390560292     5990 1302  392
222 0.050    0.22 0.06871868 0.06556113 0.640677227     5968 1301  414
223 0.050    0.23 0.07086614 0.06800360 0.681411841     5952 1298  430
224 0.050    0.24 0.07444524 0.07108883 0.630159733     5933 1293  449
225 0.050    0.25 0.07730852 0.07391696 0.632319006     5915 1289  467
226 0.050    0.26 0.07874016 0.07751639 0.893707815     5889 1287  493
227 0.050    0.27 0.08231926 0.08034452 0.806111567     5872 1282  510
228 0.050    0.28 0.08876163 0.08432961 0.545178829     5850 1273  532
229 0.050    0.29 0.09305655 0.08780049 0.475102837     5829 1267  553
230 0.050    0.30 0.09663565 0.09307109 0.648786730     5793 1262  589
231 0.050    0.31 0.09878311 0.09615632 0.750801207     5772 1259  610
232 0.050    0.32 0.10522548 0.10091271 0.587956383     5744 1250  638
233 0.050    0.33 0.11166786 0.10618331 0.492277035     5712 1241  670
234 0.050    0.34 0.11596278 0.11158247 0.598067169     5676 1235  706
235 0.050    0.35 0.11954188 0.11801003 0.880643416     5631 1230  751
236 0.050    0.36 0.12240515 0.12379483 0.897141169     5590 1226  792
237 0.050    0.37 0.13171081 0.13086515 0.952411163     5548 1213  834
238 0.050    0.38 0.13743737 0.13934953 0.853073214     5490 1205  892
239 0.050    0.39 0.14889048 0.14680550 0.840408866     5448 1189  934
240 0.050    0.40 0.15819613 0.15323306 0.597807717     5411 1176  971
241 0.050    0.41 0.16964925 0.16171744 0.395968767     5361 1160 1021
242 0.050    0.42 0.18396564 0.17084458 0.161713259     5310 1140 1072
243 0.050    0.43 0.18682892 0.17714359 0.313390030     5265 1136 1117
244 0.050    0.44 0.19470293 0.18549942 0.347701229     5211 1125 1171
245 0.050    0.45 0.20687187 0.19732613 0.340768413     5136 1108 1246
246 0.050    0.46 0.21760916 0.20606762 0.253889181     5083 1093 1299
247 0.050    0.47 0.23120974 0.21827998 0.209159645     5007 1074 1375
248 0.050    0.48 0.24123121 0.22663581 0.160519537     4956 1060 1426
249 0.050    0.49 0.25483178 0.23679136 0.086087006     4896 1041 1486
250 0.050    0.50 0.27487473 0.25118910 0.026448416     4812 1013 1570
251 0.050    0.51 0.28632785 0.26442988 0.043862731     4725  997 1657
252 0.050    0.52 0.30279170 0.27612804 0.015182915     4657  974 1725
253 0.050    0.53 0.31496063 0.28936881 0.021661888     4571  957 1811
254 0.050    0.54 0.32856120 0.30273814 0.022186522     4486  938 1896
255 0.050    0.55 0.34144596 0.31572182 0.024322076     4403  920 1979
256 0.050    0.56 0.35504653 0.32767708 0.017560545     4329  901 2053
257 0.050    0.57 0.36936292 0.34323178 0.025089999     4228  881 2154
258 0.050    0.58 0.38296349 0.35801517 0.034295612     4132  862 2250
259 0.050    0.59 0.39370079 0.37189870 0.067115943     4039  847 2343
260 0.050    0.60 0.41517538 0.38925312 0.030497829     3934  817 2448
261 0.050    0.61 0.42949177 0.40532202 0.045349462     3829  797 2553
262 0.050    0.62 0.44881890 0.42383340 0.039732857     3712  770 2670
263 0.050    0.63 0.47029349 0.44453015 0.034881401     3581  740 2801
264 0.050    0.64 0.48532570 0.46227021 0.060301024     3464  719 2918
265 0.050    0.65 0.49964209 0.47923898 0.097770838     3352  699 3030
266 0.050    0.66 0.51395848 0.49903587 0.229353049     3218  679 3164
267 0.050    0.67 0.53758053 0.51831855 0.118476463     3101  646 3281
268 0.050    0.68 0.56191840 0.53708703 0.042829080     2989  612 3393
269 0.050    0.69 0.58124553 0.55636971 0.041705695     2866  585 3516
270 0.050    0.70 0.60558339 0.57950893 0.031575793     2720  551 3662
271 0.050    0.71 0.62848962 0.59802031 0.011268238     2608  519 3774
272 0.050    0.72 0.64352183 0.62077388 0.056879437     2452  498 3930
273 0.050    0.73 0.66929134 0.64237048 0.022201274     2320  462 4062
274 0.050    0.74 0.68360773 0.65959635 0.039410723     2206  442 4176
275 0.050    0.75 0.69720830 0.67900758 0.114771690     2074  423 4308
276 0.050    0.76 0.72083035 0.69983288 0.063134006     1945  390 4437
277 0.050    0.77 0.74015748 0.72142949 0.090848230     1804  363 4578
278 0.050    0.78 0.76163207 0.74302610 0.084840723     1666  333 4716
279 0.050    0.79 0.77881174 0.76179458 0.106576637     1544  309 4838
280 0.050    0.80 0.79455977 0.77902044 0.131072969     1432  287 4950
281 0.050    0.81 0.80243379 0.79778892 0.659620158     1297  276 5085
282 0.050    0.82 0.82176092 0.81578609 0.549905114     1184  249 5198
283 0.050    0.83 0.83965641 0.83262630 0.460797967     1078  224 5304
284 0.050    0.84 0.85540444 0.84869521 0.464546456      975  202 5407
285 0.050    0.85 0.87186829 0.86617817 0.518097163      862  179 5520
286 0.050    0.86 0.89047960 0.88301838 0.361764602      757  153 5625
287 0.050    0.87 0.90551181 0.89613061 0.222297192      676  132 5706
288 0.050    0.88 0.91410165 0.90821442 0.429374395      594  120 5788
289 0.050    0.89 0.92555476 0.92132665 0.553053247      508  104 5874
290 0.050    0.90 0.93557623 0.93148220 0.541689881      443   90 5939
291 0.050    0.91 0.94559771 0.94073788 0.431407667      385   76 5997
292 0.050    0.92 0.95633500 0.95192184 0.434089359      313   61 6069
293 0.050    0.93 0.96420902 0.96040622 0.466013710      258   50 6124
294 0.050    0.94 0.96921976 0.96747654 0.747254132      210   43 6172
295 0.050    0.95 0.97924123 0.97544672 0.359490585      162   29 6220
296 0.050    0.96 0.98496779 0.98225993 0.462585101      117   21 6265
297 0.050    0.97 0.98783107 0.98753053 1.000000000       80   17 6302
298 0.050    0.98 0.99069435 0.99138707 0.881146735       54   13 6328
299 0.050    0.99 0.99570508 0.99601491 1.000000000       25    6 6357
300 0.050    1.00 1.00000000 1.00000000 0.000000000        0    0 6382
301 0.075    0.01 0.01977401 0.02082530 0.796628543     5882 1735  127
302 0.075    0.02 0.02598870 0.02686721 0.859943816     5846 1724  163
303 0.075    0.03 0.02768362 0.02879547 0.812346794     5834 1721  175
304 0.075    0.04 0.03107345 0.03226636 0.805197555     5813 1715  196
305 0.075    0.05 0.03333333 0.03432318 0.852456701     5801 1711  208
306 0.075    0.06 0.03615819 0.03689420 0.908311928     5786 1706  223
307 0.075    0.07 0.03728814 0.03817971 0.879069770     5778 1704  231
308 0.075    0.08 0.04011299 0.03959378 0.953659993     5772 1699  237
309 0.075    0.09 0.04293785 0.04062219 0.622012841     5769 1694  240
310 0.075    0.10 0.04406780 0.04139350 0.565451557     5765 1692  244
311 0.075    0.11 0.04632768 0.04280756 0.443899609     5758 1688  251
312 0.075    0.12 0.04802260 0.04486438 0.506059096     5745 1685  264
313 0.075    0.13 0.04802260 0.04537858 0.587043768     5741 1685  268
314 0.075    0.14 0.04915254 0.04679265 0.637744384     5732 1683  277
315 0.075    0.15 0.04971751 0.04859236 0.851189620     5719 1682  290
316 0.075    0.16 0.05197740 0.05077773 0.841498037     5706 1678  303
317 0.075    0.17 0.05536723 0.05360586 0.753295983     5690 1672  319
318 0.075    0.18 0.05762712 0.05489137 0.606146321     5684 1668  325
319 0.075    0.19 0.06214689 0.05810515 0.441773513     5667 1660  342
320 0.075    0.20 0.06384181 0.06016197 0.494031118     5654 1657  355
321 0.075    0.21 0.06723164 0.06260445 0.390612787     5641 1651  368
322 0.075    0.22 0.06779661 0.06556113 0.705651128     5619 1650  390
323 0.075    0.23 0.07005650 0.06800360 0.736398267     5604 1646  405
324 0.075    0.24 0.07401130 0.07108883 0.622882734     5587 1639  422
325 0.075    0.25 0.07627119 0.07391696 0.704657125     5569 1635  440
326 0.075    0.26 0.07796610 0.07751639 0.976119186     5544 1632  465
327 0.075    0.27 0.08135593 0.08034452 0.897861218     5528 1626  481
328 0.075    0.28 0.08757062 0.08432961 0.610303446     5508 1615  501
329 0.075    0.29 0.09096045 0.08780049 0.626467260     5487 1609  522
330 0.075    0.30 0.09548023 0.09307109 0.726047256     5454 1601  555
331 0.075    0.31 0.09774011 0.09615632 0.832655947     5434 1597  575
332 0.075    0.32 0.10282486 0.10091271 0.795648784     5406 1588  603
333 0.075    0.33 0.10790960 0.10618331 0.822494059     5374 1579  635
334 0.075    0.34 0.11186441 0.11158247 1.000000000     5339 1572  670
335 0.075    0.35 0.11694915 0.11801003 0.908055016     5298 1563  711
336 0.075    0.36 0.11977401 0.12379483 0.586895901     5258 1558  751
337 0.075    0.37 0.12881356 0.13086515 0.801737412     5219 1542  790
338 0.075    0.38 0.13446328 0.13934953 0.524549616     5163 1532  846
339 0.075    0.39 0.14406780 0.14680550 0.739828948     5122 1515  887
340 0.075    0.40 0.15310734 0.15323306 1.000000000     5088 1499  921
341 0.075    0.41 0.16327684 0.16171744 0.868149560     5040 1481  969
342 0.075    0.42 0.17740113 0.17084458 0.424897371     4994 1456 1015
343 0.075    0.43 0.18135593 0.17714359 0.622211279     4952 1449 1057
344 0.075    0.44 0.18983051 0.18549942 0.618074835     4902 1434 1107
345 0.075    0.45 0.20282486 0.19732613 0.530398516     4833 1411 1176
346 0.075    0.46 0.21412429 0.20606762 0.357552717     4785 1391 1224
347 0.075    0.47 0.22937853 0.21827998 0.210066191     4717 1364 1292
348 0.075    0.48 0.24124294 0.22663581 0.101452487     4673 1343 1336
349 0.075    0.49 0.25310734 0.23679136 0.071013620     4615 1322 1394
350 0.075    0.50 0.27344633 0.25118910 0.015291205     4539 1286 1470
351 0.075    0.51 0.28418079 0.26442988 0.034595961     4455 1267 1554
352 0.075    0.52 0.30056497 0.27612804 0.009704679     4393 1238 1616
353 0.075    0.53 0.31525424 0.28936881 0.006878989     4316 1212 1693
354 0.075    0.54 0.32994350 0.30273814 0.005031207     4238 1186 1771
355 0.075    0.55 0.34237288 0.31572182 0.006615614     4159 1164 1850
356 0.075    0.56 0.35536723 0.32767708 0.005187319     4089 1141 1920
357 0.075    0.57 0.36836158 0.34323178 0.012241266     3991 1118 2018
358 0.075    0.58 0.38135593 0.35801517 0.021318480     3899 1095 2110
359 0.075    0.59 0.39265537 0.37189870 0.042579886     3811 1075 2198
360 0.075    0.60 0.41355932 0.38925312 0.018347593     3713 1038 2296
361 0.075    0.61 0.42542373 0.40532202 0.053312368     3609 1017 2400
362 0.075    0.62 0.44406780 0.42383340 0.053275421     3498  984 2511
363 0.075    0.63 0.46779661 0.44453015 0.026823813     3379  942 2630
364 0.075    0.64 0.48361582 0.46227021 0.043148010     3269  914 2740
365 0.075    0.65 0.49717514 0.47923898 0.090729955     3161  890 2848
366 0.075    0.66 0.51242938 0.49903587 0.209404071     3034  863 2975
367 0.075    0.67 0.53502825 0.51831855 0.115547588     2924  823 3085
368 0.075    0.68 0.55819209 0.53708703 0.045609819     2819  782 3190
369 0.075    0.69 0.57909605 0.55636971 0.030581096     2706  745 3303
370 0.075    0.70 0.60169492 0.57950893 0.033671015     2566  705 3443
371 0.075    0.71 0.62259887 0.59802031 0.017689791     2459  668 3550
372 0.075    0.72 0.64067797 0.62077388 0.052889169     2314  636 3695
373 0.075    0.73 0.66327684 0.64237048 0.039425391     2186  596 3823
374 0.075    0.74 0.67909605 0.65959635 0.052217090     2080  568 3929
375 0.075    0.75 0.69152542 0.67900758 0.209651335     1951  546 4058
376 0.075    0.76 0.71412429 0.69983288 0.143440504     1829  506 4180
377 0.075    0.77 0.73502825 0.72142949 0.155058573     1698  469 4311
378 0.075    0.78 0.75536723 0.74302610 0.186504671     1566  433 4443
379 0.075    0.79 0.77344633 0.76179458 0.201400666     1452  401 4557
380 0.075    0.80 0.78870056 0.77902044 0.278269144     1345  374 4664
381 0.075    0.81 0.80056497 0.79778892 0.766327835     1220  353 4789
382 0.075    0.82 0.81977401 0.81578609 0.647276787     1114  319 4895
383 0.075    0.83 0.83672316 0.83262630 0.624767210     1013  289 4996
384 0.075    0.84 0.85197740 0.84869521 0.688637508      915  262 5094
385 0.075    0.85 0.86666667 0.86617817 0.976892902      805  236 5204
386 0.075    0.86 0.88531073 0.88301838 0.764677465      707  203 5302
387 0.075    0.87 0.90169492 0.89613061 0.407269505      634  174 5375
388 0.075    0.88 0.91355932 0.90821442 0.401294127      561  153 5448
389 0.075    0.89 0.92485876 0.92132665 0.563415188      479  133 5530
390 0.075    0.90 0.93615819 0.93148220 0.405142080      420  113 5589
391 0.075    0.91 0.94576271 0.94073788 0.336336319      365   96 5644
392 0.075    0.92 0.95536723 0.95192184 0.479121663      295   79 5714
393 0.075    0.93 0.96384181 0.96040622 0.438927348      244   64 5765
394 0.075    0.94 0.96892655 0.96747654 0.752714444      198   55 5811
395 0.075    0.95 0.97853107 0.97544672 0.386138838      153   38 5856
396 0.075    0.96 0.98361582 0.98225993 0.697097433      109   29 5900
397 0.075    0.97 0.98757062 0.98753053 1.000000000       75   22 5934
398 0.075    0.98 0.99039548 0.99138707 0.713371384       50   17 5959
399 0.075    0.99 0.99604520 0.99601491 1.000000000       24    7 5985
400 0.075    1.00 1.00000000 1.00000000 0.000000000        0    0 6009
401 0.100    0.01 0.01912046 0.02082530 0.582929172     5565 2052  122
402 0.100    0.02 0.02629063 0.02686721 0.911078754     5533 2037  154
403 0.100    0.03 0.02772467 0.02879547 0.790181210     5521 2034  166
404 0.100    0.04 0.03202677 0.03226636 0.999858998     5503 2025  184
405 0.100    0.05 0.03393881 0.03432318 0.965932756     5491 2021  196
406 0.100    0.06 0.03728489 0.03689420 0.965664871     5478 2014  209
407 0.100    0.07 0.03824092 0.03817971 1.000000000     5470 2012  217
408 0.100    0.08 0.04063098 0.03959378 0.826680282     5464 2007  223
409 0.100    0.09 0.04302103 0.04062219 0.558375514     5461 2002  226
410 0.100    0.10 0.04445507 0.04139350 0.448461685     5458 1999  229
411 0.100    0.11 0.04636711 0.04280756 0.380210816     5451 1995  236
412 0.100    0.12 0.04827916 0.04486438 0.411835487     5439 1991  248
413 0.100    0.13 0.04827916 0.04537858 0.493933610     5435 1991  252
414 0.100    0.14 0.04923518 0.04679265 0.576753839     5426 1989  261
415 0.100    0.15 0.05066922 0.04859236 0.647499499     5415 1986  272
416 0.100    0.16 0.05258126 0.05077773 0.703048938     5402 1982  285
417 0.100    0.17 0.05544933 0.05360586 0.703161773     5386 1976  301
418 0.100    0.18 0.05736138 0.05489137 0.600298813     5380 1972  307
419 0.100    0.19 0.06166348 0.05810515 0.447852742     5364 1963  323
420 0.100    0.20 0.06357553 0.06016197 0.475128652     5352 1959  335
421 0.100    0.21 0.06644359 0.06260445 0.426624727     5339 1953  348
422 0.100    0.22 0.06739962 0.06556113 0.729578082     5318 1951  369
423 0.100    0.23 0.06978967 0.06800360 0.742360573     5304 1946  383
424 0.100    0.24 0.07361377 0.07108883 0.634176101     5288 1938  399
425 0.100    0.25 0.07600382 0.07391696 0.705571551     5271 1933  416
426 0.100    0.26 0.07887189 0.07751639 0.823264484     5249 1927  438
427 0.100    0.27 0.08269598 0.08034452 0.677616076     5235 1919  452
428 0.100    0.28 0.08891013 0.08432961 0.403287777     5217 1906  470
429 0.100    0.29 0.09321224 0.08780049 0.328197102     5199 1897  488
430 0.100    0.30 0.09703633 0.09307109 0.492660180     5166 1889  521
431 0.100    0.31 0.09894837 0.09615632 0.643177878     5146 1885  541
432 0.100    0.32 0.10468451 0.10091271 0.530396202     5121 1873  566
433 0.100    0.33 0.10946463 0.10618331 0.597315424     5090 1863  597
434 0.100    0.34 0.11328872 0.11158247 0.803139521     5056 1855  631
435 0.100    0.35 0.11806883 0.11801003 1.000000000     5016 1845  671
436 0.100    0.36 0.12141491 0.12379483 0.728040730     4978 1838  709
437 0.100    0.37 0.12954111 0.13086515 0.863356290     4940 1821  747
438 0.100    0.38 0.13575526 0.13934953 0.604264942     4887 1808  800
439 0.100    0.39 0.14531549 0.14680550 0.850023069     4849 1788  838
440 0.100    0.40 0.15344168 0.15323306 1.000000000     4816 1771  871
441 0.100    0.41 0.16395793 0.16171744 0.771211779     4772 1749  915
442 0.100    0.42 0.17590822 0.17084458 0.492889556     4726 1724  961
443 0.100    0.43 0.17973231 0.17714359 0.741986229     4685 1716 1002
444 0.100    0.44 0.18785851 0.18549942 0.770464527     4637 1699 1050
445 0.100    0.45 0.19980880 0.19732613 0.762976054     4570 1674 1117
446 0.100    0.46 0.21080306 0.20606762 0.552066985     4525 1651 1162
447 0.100    0.47 0.22514340 0.21827998 0.390970287     4460 1621 1227
448 0.100    0.48 0.23613767 0.22663581 0.236588325     4418 1598 1269
449 0.100    0.49 0.24713193 0.23679136 0.203687401     4362 1575 1325
450 0.100    0.50 0.26768642 0.25118910 0.044925584     4293 1532 1394
451 0.100    0.51 0.27772467 0.26442988 0.113292010     4211 1511 1476
452 0.100    0.52 0.29445507 0.27612804 0.030445671     4155 1476 1532
453 0.100    0.53 0.30831740 0.28936881 0.027308793     4081 1447 1606
454 0.100    0.54 0.32456979 0.30273814 0.011935062     4011 1413 1676
455 0.100    0.55 0.33699809 0.31572182 0.015471470     3936 1387 1751
456 0.100    0.56 0.34942639 0.32767708 0.014225390     3869 1361 1818
457 0.100    0.57 0.36233270 0.34323178 0.033575146     3775 1334 1912
458 0.100    0.58 0.37715105 0.35801517 0.034985899     3691 1303 1996
459 0.100    0.59 0.38766730 0.37189870 0.085644476     3605 1281 2082
460 0.100    0.60 0.40965583 0.38925312 0.026952688     3516 1235 2171
461 0.100    0.61 0.42208413 0.40532202 0.071808817     3417 1209 2270
462 0.100    0.62 0.44168260 0.42383340 0.056609899     3314 1168 2373
463 0.100    0.63 0.46558317 0.44453015 0.025047998     3203 1118 2484
464 0.100    0.64 0.48183556 0.46227021 0.038118329     3099 1084 2588
465 0.100    0.65 0.49856597 0.47923898 0.040960540     3002 1049 2685
466 0.100    0.66 0.51529637 0.49903587 0.086511221     2883 1014 2804
467 0.100    0.67 0.53680688 0.51831855 0.050730442     2778  969 2909
468 0.100    0.68 0.55831740 0.53708703 0.024321816     2677  924 3010
469 0.100    0.69 0.57839388 0.55636971 0.018992182     2569  882 3118
470 0.100    0.70 0.60133843 0.57950893 0.019300621     2437  834 3250
471 0.100    0.71 0.62189293 0.59802031 0.009922349     2336  791 3351
472 0.100    0.72 0.63957935 0.62077388 0.040659625     2196  754 3491
473 0.100    0.73 0.66108987 0.64237048 0.039156325     2073  709 3614
474 0.100    0.74 0.67638623 0.65959635 0.061696705     1971  677 3716
475 0.100    0.75 0.69263862 0.67900758 0.124910138     1854  643 3833
476 0.100    0.76 0.71462715 0.69983288 0.089356759     1738  597 3949
477 0.100    0.77 0.73565966 0.72142949 0.095015354     1614  553 4073
478 0.100    0.78 0.75717017 0.74302610 0.088705269     1491  508 4196
479 0.100    0.79 0.77533461 0.76179458 0.094862268     1383  470 4304
480 0.100    0.80 0.79158700 0.77902044 0.111974828     1283  436 4404
481 0.100    0.81 0.80497132 0.79778892 0.355093583     1165  408 4522
482 0.100    0.82 0.82313576 0.81578609 0.326489610     1063  370 4624
483 0.100    0.83 0.84130019 0.83262630 0.226785578      970  332 4717
484 0.100    0.84 0.85659656 0.84869521 0.252694959      877  300 4810
485 0.100    0.85 0.87141491 0.86617817 0.432307641      772  269 4915
486 0.100    0.86 0.88862333 0.88301838 0.371800295      677  233 5010
487 0.100    0.87 0.90487572 0.89613061 0.135849145      609  199 5078
488 0.100    0.88 0.91634799 0.90821442 0.143556367      539  175 5148
489 0.100    0.89 0.92638623 0.92132665 0.338158247      458  154 5229
490 0.100    0.90 0.93690249 0.93148220 0.272594015      401  132 5286
491 0.100    0.91 0.94741874 0.94073788 0.144441766      351  110 5336
492 0.100    0.92 0.95745698 0.95192184 0.185404439      285   89 5402
493 0.100    0.93 0.96510516 0.96040622 0.221157171      235   73 5452
494 0.100    0.94 0.96988528 0.96747654 0.512907181      190   63 5497
495 0.100    0.95 0.97848948 0.97544672 0.332476187      146   45 5541
496 0.100    0.96 0.98470363 0.98225993 0.371628556      106   32 5581
497 0.100    0.97 0.98852772 0.98753053 0.714743610       73   24 5614
498 0.100    0.98 0.99091778 0.99138707 0.893948843       48   19 5639
499 0.100    0.99 0.99617591 0.99601491 1.000000000       23    8 5664
500 0.100    1.00 1.00000000 1.00000000 0.000000000        0    0 5687
    Dboth
1      11
2      12
3      14
4      15
5      16
6      17
7      18
8      20
9      22
10     22
11     24
12     24
13     24
14     24
15     25
16     27
17     29
18     29
19     30
20     30
21     32
22     32
23     33
24     36
25     38
26     38
27     39
28     44
29     47
30     47
31     48
32     49
33     50
34     51
35     54
36     55
37     60
38     63
39     67
40     71
41     76
42     84
43     85
44     88
45     94
46     96
47    101
48    108
49    115
50    121
51    129
52    136
53    141
54    147
55    150
56    154
57    163
58    173
59    178
60    191
61    196
62    204
63    217
64    225
65    234
66    242
67    255
68    264
69    275
70    289
71    301
72    307
73    316
74    319
75    325
76    339
77    344
78    360
79    366
80    373
81    376
82    381
83    389
84    399
85    403
86    413
87    421
88    422
89    426
90    431
91    432
92    438
93    441
94    441
95    448
96    451
97    451
98    451
99    456
100   457
101    17
102    23
103    26
104    28
105    30
106    34
107    36
108    38
109    40
110    40
111    44
112    45
113    45
114    45
115    46
116    48
117    52
118    54
119    57
120    60
121    64
122    65
123    68
124    72
125    74
126    76
127    79
128    85
129    89
130    92
131    94
132    98
133   103
134   107
135   111
136   112
137   120
138   126
139   138
140   147
141   156
142   170
143   172
144   177
145   190
146   198
147   209
148   219
149   234
150   250
151   266
152   282
153   292
154   308
155   315
156   328
157   343
158   359
159   368
160   388
161   402
162   419
163   438
164   452
165   469
166   483
167   502
168   523
169   543
170   564
171   587
172   598
173   624
174   633
175   646
176   670
177   685
178   709
179   726
180   737
181   744
182   761
183   774
184   791
185   804
186   824
187   837
188   843
189   854
190   863
191   872
192   883
193   888
194   890
195   900
196   906
197   909
198   910
199   916
200   920
201    28
202    37
203    40
204    45
205    48
206    52
207    54
208    58
209    60
210    61
211    65
212    68
213    68
214    68
215    69
216    73
217    79
218    82
219    87
220    90
221    95
222    96
223    99
224   104
225   108
226   110
227   115
228   124
229   130
230   135
231   138
232   147
233   156
234   162
235   167
236   171
237   184
238   192
239   208
240   221
241   237
242   257
243   261
244   272
245   289
246   304
247   323
248   337
249   356
250   384
251   400
252   423
253   440
254   459
255   477
256   496
257   516
258   535
259   550
260   580
261   600
262   627
263   657
264   678
265   698
266   718
267   751
268   785
269   812
270   846
271   878
272   899
273   935
274   955
275   974
276  1007
277  1034
278  1064
279  1088
280  1110
281  1121
282  1148
283  1173
284  1195
285  1218
286  1244
287  1265
288  1277
289  1293
290  1307
291  1321
292  1336
293  1347
294  1354
295  1368
296  1376
297  1380
298  1384
299  1391
300  1397
301    35
302    46
303    49
304    55
305    59
306    64
307    66
308    71
309    76
310    78
311    82
312    85
313    85
314    87
315    88
316    92
317    98
318   102
319   110
320   113
321   119
322   120
323   124
324   131
325   135
326   138
327   144
328   155
329   161
330   169
331   173
332   182
333   191
334   198
335   207
336   212
337   228
338   238
339   255
340   271
341   289
342   314
343   321
344   336
345   359
346   379
347   406
348   427
349   448
350   484
351   503
352   532
353   558
354   584
355   606
356   629
357   652
358   675
359   695
360   732
361   753
362   786
363   828
364   856
365   880
366   907
367   947
368   988
369  1025
370  1065
371  1102
372  1134
373  1174
374  1202
375  1224
376  1264
377  1301
378  1337
379  1369
380  1396
381  1417
382  1451
383  1481
384  1508
385  1534
386  1567
387  1596
388  1617
389  1637
390  1657
391  1674
392  1691
393  1706
394  1715
395  1732
396  1741
397  1748
398  1753
399  1763
400  1770
401    40
402    55
403    58
404    67
405    71
406    78
407    80
408    85
409    90
410    93
411    97
412   101
413   101
414   103
415   106
416   110
417   116
418   120
419   129
420   133
421   139
422   141
423   146
424   154
425   159
426   165
427   173
428   186
429   195
430   203
431   207
432   219
433   229
434   237
435   247
436   254
437   271
438   284
439   304
440   321
441   343
442   368
443   376
444   393
445   418
446   441
447   471
448   494
449   517
450   560
451   581
452   616
453   645
454   679
455   705
456   731
457   758
458   789
459   811
460   857
461   883
462   924
463   974
464  1008
465  1043
466  1078
467  1123
468  1168
469  1210
470  1258
471  1301
472  1338
473  1383
474  1415
475  1449
476  1495
477  1539
478  1584
479  1622
480  1656
481  1684
482  1722
483  1760
484  1792
485  1823
486  1859
487  1893
488  1917
489  1938
490  1960
491  1982
492  2003
493  2019
494  2029
495  2047
496  2060
497  2068
498  2073
499  2084
500  2092
enrichment.plotter(gene.hic.filt, "weighted_Z.s2post.H", "adj.P.Val", "FDR for Weighted p-val Combine of Hi-C Contacts Overlapping Gene, Human")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR  prop.obs  prop.exp     chisq.p Dneither  DE DHiC Dboth
1   0.010    0.01 0.7297872 0.6813498 0.022962069     2347 127 4947   343
2   0.010    0.02 0.7446809 0.6926842 0.013543632     2266 120 5028   350
3   0.010    0.03 0.7489362 0.6971922 0.013621159     2233 118 5061   352
4   0.010    0.04 0.7531915 0.7028594 0.015893354     2191 116 5103   354
5   0.010    0.05 0.7574468 0.7064657 0.014214503     2165 114 5129   356
6   0.010    0.06 0.7638298 0.7102009 0.009553302     2139 111 5155   359
7   0.010    0.07 0.7638298 0.7122617 0.012586039     2123 111 5171   359
8   0.010    0.08 0.7638298 0.7145801 0.017009793     2105 111 5189   359
9   0.010    0.09 0.7659574 0.7172849 0.018044986     2085 110 5209   360
10  0.010    0.10 0.7659574 0.7206337 0.027359231     2059 110 5235   360
11  0.010    0.11 0.7680851 0.7217929 0.023976287     2051 109 5243   361
12  0.010    0.12 0.7702128 0.7237249 0.023077436     2037 108 5257   362
13  0.010    0.13 0.7702128 0.7252705 0.027902316     2025 108 5269   362
14  0.010    0.14 0.7702128 0.7269449 0.034108528     2012 108 5282   362
15  0.010    0.15 0.7723404 0.7299073 0.037160470     1990 107 5304   363
16  0.010    0.16 0.7744681 0.7314529 0.034247052     1979 106 5315   364
17  0.010    0.17 0.7765957 0.7344152 0.037310268     1957 105 5337   365
18  0.010    0.18 0.7765957 0.7349304 0.039634673     1953 105 5341   365
19  0.010    0.19 0.7808511 0.7362184 0.027011163     1945 103 5349   367
20  0.010    0.20 0.7829787 0.7373776 0.023591758     1937 102 5357   368
21  0.010    0.21 0.7851064 0.7382792 0.019879701     1931 101 5363   369
22  0.010    0.22 0.7851064 0.7390520 0.021935890     1925 101 5369   369
23  0.010    0.23 0.7851064 0.7402112 0.025374185     1916 101 5378   369
24  0.010    0.24 0.7851064 0.7411128 0.028368962     1909 101 5385   369
25  0.010    0.25 0.7851064 0.7422720 0.032673318     1900 101 5394   369
26  0.010    0.26 0.7851064 0.7434312 0.037538532     1891 101 5403   369
27  0.010    0.27 0.7872340 0.7452344 0.035611594     1878 100 5416   370
28  0.010    0.28 0.7914894 0.7465224 0.023981639     1870  98 5424   372
29  0.010    0.29 0.7914894 0.7471664 0.026002062     1865  98 5429   372
30  0.010    0.30 0.7914894 0.7479392 0.028623804     1859  98 5435   372
31  0.010    0.31 0.7914894 0.7489696 0.032479796     1851  98 5443   372
32  0.010    0.32 0.7914894 0.7506440 0.039718525     1838  98 5456   372
33  0.010    0.33 0.7914894 0.7510304 0.041575605     1835  98 5459   372
34  0.010    0.34 0.7914894 0.7520608 0.046900036     1827  98 5467   372
35  0.010    0.35 0.7914894 0.7528336 0.051269969     1821  98 5473   372
36  0.010    0.36 0.7914894 0.7536064 0.055984905     1815  98 5479   372
37  0.010    0.37 0.7914894 0.7545080 0.061949295     1808  98 5486   372
38  0.010    0.38 0.7936170 0.7552808 0.052484919     1803  97 5491   373
39  0.010    0.39 0.7936170 0.7559248 0.056477919     1798  97 5496   373
40  0.010    0.40 0.7936170 0.7563112 0.058996158     1795  97 5499   373
41  0.010    0.41 0.7957447 0.7572128 0.050635401     1789  96 5505   374
42  0.010    0.42 0.7978723 0.7587584 0.046674719     1778  95 5516   375
43  0.010    0.43 0.8000000 0.7599176 0.041029756     1770  94 5524   376
44  0.010    0.44 0.8000000 0.7604328 0.043619019     1766  94 5528   376
45  0.010    0.45 0.8000000 0.7608192 0.045652753     1763  94 5531   376
46  0.010    0.46 0.8000000 0.7609480 0.046348640     1762  94 5532   376
47  0.010    0.47 0.8021277 0.7614632 0.037681343     1759  93 5535   377
48  0.010    0.48 0.8063830 0.7630088 0.026048606     1749  91 5545   379
49  0.010    0.49 0.8063830 0.7636528 0.028259074     1744  91 5550   379
50  0.010    0.50 0.8063830 0.7642968 0.030633396     1739  91 5555   379
51  0.010    0.51 0.8085106 0.7649408 0.024954217     1735  90 5559   380
52  0.010    0.52 0.8085106 0.7653272 0.026216077     1732  90 5562   380
53  0.010    0.53 0.8085106 0.7664863 0.030346702     1723  90 5571   380
54  0.010    0.54 0.8085106 0.7667439 0.031338907     1721  90 5573   380
55  0.010    0.55 0.8148936 0.7677743 0.014703701     1716  87 5578   383
56  0.010    0.56 0.8148936 0.7689335 0.017202427     1707  87 5587   383
57  0.010    0.57 0.8170213 0.7700927 0.014767418     1699  86 5595   384
58  0.010    0.58 0.8191489 0.7713807 0.012861861     1690  85 5604   385
59  0.010    0.59 0.8191489 0.7721535 0.014312251     1684  85 5610   385
60  0.010    0.60 0.8191489 0.7727975 0.015631825     1679  85 5615   385
61  0.010    0.61 0.8191489 0.7736991 0.017663132     1672  85 5622   385
62  0.010    0.62 0.8191489 0.7749871 0.020975778     1662  85 5632   385
63  0.010    0.63 0.8191489 0.7761463 0.024419928     1653  85 5641   385
64  0.010    0.64 0.8191489 0.7769191 0.026986660     1647  85 5647   385
65  0.010    0.65 0.8191489 0.7780783 0.031284784     1638  85 5656   385
66  0.010    0.66 0.8212766 0.7791087 0.026679119     1631  84 5663   386
67  0.010    0.67 0.8234043 0.7796239 0.021163917     1628  83 5666   387
68  0.010    0.68 0.8234043 0.7803967 0.023439009     1622  83 5672   387
69  0.010    0.69 0.8234043 0.7818135 0.028180843     1611  83 5683   387
70  0.010    0.70 0.8255319 0.7821999 0.021991057     1609  82 5685   388
71  0.010    0.71 0.8255319 0.7827151 0.023540998     1605  82 5689   388
72  0.010    0.72 0.8255319 0.7831015 0.024766509     1602  82 5692   388
73  0.010    0.73 0.8255319 0.7842607 0.028789937     1593  82 5701   388
74  0.010    0.74 0.8255319 0.7852911 0.032840697     1585  82 5709   388
75  0.010    0.75 0.8255319 0.7864503 0.037989822     1576  82 5718   388
76  0.010    0.76 0.8255319 0.7883823 0.048147635     1561  82 5733   388
77  0.010    0.77 0.8255319 0.7892839 0.053643288     1554  82 5740   388
78  0.010    0.78 0.8255319 0.7904431 0.061496247     1545  82 5749   388
79  0.010    0.79 0.8255319 0.7916023 0.070312155     1536  82 5758   388
80  0.010    0.80 0.8276596 0.7931479 0.064745005     1525  81 5769   389
81  0.010    0.81 0.8297872 0.7944359 0.057727224     1516  80 5778   390
82  0.010    0.82 0.8297872 0.7953375 0.064187200     1509  80 5785   390
83  0.010    0.83 0.8319149 0.7962391 0.054605725     1503  79 5791   391
84  0.010    0.84 0.8319149 0.7972694 0.061719298     1495  79 5799   391
85  0.010    0.85 0.8319149 0.7977846 0.065564261     1491  79 5803   391
86  0.010    0.86 0.8361702 0.7994590 0.046448112     1480  77 5814   393
87  0.010    0.87 0.8382979 0.8007470 0.041039122     1471  76 5823   394
88  0.010    0.88 0.8425532 0.8015198 0.024999256     1467  74 5827   396
89  0.010    0.89 0.8425532 0.8029366 0.030173465     1456  74 5838   396
90  0.010    0.90 0.8446809 0.8037094 0.024619524     1451  73 5843   397
91  0.010    0.91 0.8446809 0.8048686 0.028747040     1442  73 5852   397
92  0.010    0.92 0.8510638 0.8080886 0.017291017     1420  70 5874   400
93  0.010    0.93 0.8510638 0.8102782 0.023450725     1403  70 5891   400
94  0.010    0.94 0.8553191 0.8129830 0.017909660     1384  68 5910   402
95  0.010    0.95 0.8553191 0.8162030 0.027987326     1359  68 5935   402
96  0.010    0.96 0.8553191 0.8201958 0.047282703     1328  68 5966   402
97  0.010    0.97 0.8595745 0.8247038 0.046729618     1295  66 5999   404
98  0.010    0.98 0.8680851 0.8297269 0.026468035     1260  62 6034   408
99  0.010    0.99 0.8765957 0.8362957 0.017699671     1213  58 6081   412
100 0.010    1.00 1.0000000 1.0000000 0.000000000        0   0 7294   470
101 0.025    0.01 0.7009751 0.6813498 0.184984033     2198 276 4643   647
102 0.025    0.02 0.7139762 0.6926842 0.145498203     2122 264 4719   659
103 0.025    0.03 0.7172264 0.6971922 0.169730487     2090 261 4751   662
104 0.025    0.04 0.7237270 0.7028594 0.150002343     2052 255 4789   668
105 0.025    0.05 0.7291441 0.7064657 0.115641732     2029 250 4812   673
106 0.025    0.06 0.7334778 0.7102009 0.104809992     2004 246 4837   677
107 0.025    0.07 0.7356446 0.7122617 0.102470569     1990 244 4851   679
108 0.025    0.08 0.7367281 0.7145801 0.121515569     1973 243 4868   680
109 0.025    0.09 0.7399783 0.7172849 0.111361836     1955 240 4886   683
110 0.025    0.10 0.7399783 0.7206337 0.174994604     1929 240 4912   683
111 0.025    0.11 0.7432286 0.7217929 0.131275907     1923 237 4918   686
112 0.025    0.12 0.7443120 0.7237249 0.146803912     1909 236 4932   687
113 0.025    0.13 0.7443120 0.7252705 0.179799931     1897 236 4944   687
114 0.025    0.14 0.7453954 0.7269449 0.193259834     1885 235 4956   688
115 0.025    0.15 0.7497291 0.7299073 0.159898146     1866 231 4975   692
116 0.025    0.16 0.7508126 0.7314529 0.169375847     1855 230 4986   693
117 0.025    0.17 0.7518960 0.7344152 0.214470478     1833 229 5008   694
118 0.025    0.18 0.7518960 0.7349304 0.228451613     1829 229 5012   694
119 0.025    0.19 0.7540628 0.7362184 0.203805540     1821 227 5020   696
120 0.025    0.20 0.7562297 0.7373776 0.178078487     1814 225 5027   698
121 0.025    0.21 0.7573131 0.7382792 0.173331575     1808 224 5033   699
122 0.025    0.22 0.7573131 0.7390520 0.191578870     1802 224 5039   699
123 0.025    0.23 0.7573131 0.7402112 0.221612627     1793 224 5048   699
124 0.025    0.24 0.7583965 0.7411128 0.216061875     1787 223 5054   700
125 0.025    0.25 0.7583965 0.7422720 0.248869431     1778 223 5063   700
126 0.025    0.26 0.7583965 0.7434312 0.285116821     1769 223 5072   700
127 0.025    0.27 0.7594800 0.7452344 0.308721223     1756 222 5085   701
128 0.025    0.28 0.7616468 0.7465224 0.277921383     1748 220 5093   703
129 0.025    0.29 0.7627302 0.7471664 0.263295666     1744 219 5097   704
130 0.025    0.30 0.7638137 0.7479392 0.253069893     1739 218 5102   705
131 0.025    0.31 0.7648971 0.7489696 0.250787842     1732 217 5109   706
132 0.025    0.32 0.7659805 0.7506440 0.268384253     1720 216 5121   707
133 0.025    0.33 0.7659805 0.7510304 0.280835937     1717 216 5124   707
134 0.025    0.34 0.7659805 0.7520608 0.316000398     1709 216 5132   707
135 0.025    0.35 0.7659805 0.7528336 0.344261848     1703 216 5138   707
136 0.025    0.36 0.7659805 0.7536064 0.374148486     1697 216 5144   707
137 0.025    0.37 0.7659805 0.7545080 0.411062480     1690 216 5151   707
138 0.025    0.38 0.7670639 0.7552808 0.397393373     1685 215 5156   708
139 0.025    0.39 0.7670639 0.7559248 0.424571557     1680 215 5161   708
140 0.025    0.40 0.7670639 0.7563112 0.441410739     1677 215 5164   708
141 0.025    0.41 0.7681473 0.7572128 0.432742611     1671 214 5170   709
142 0.025    0.42 0.7713976 0.7587584 0.360101314     1662 211 5179   712
143 0.025    0.43 0.7724810 0.7599176 0.362328462     1654 210 5187   713
144 0.025    0.44 0.7735645 0.7604328 0.339731655     1651 209 5190   714
145 0.025    0.45 0.7735645 0.7608192 0.354494285     1648 209 5193   714
146 0.025    0.46 0.7735645 0.7609480 0.359507460     1647 209 5194   714
147 0.025    0.47 0.7746479 0.7614632 0.336987390     1644 208 5197   715
148 0.025    0.48 0.7768147 0.7630088 0.312701748     1634 206 5207   717
149 0.025    0.49 0.7768147 0.7636528 0.336323277     1629 206 5212   717
150 0.025    0.50 0.7768147 0.7642968 0.361109002     1624 206 5217   717
151 0.025    0.51 0.7789816 0.7649408 0.302843665     1621 204 5220   719
152 0.025    0.52 0.7789816 0.7653272 0.316617859     1618 204 5223   719
153 0.025    0.53 0.7789816 0.7664863 0.360467814     1609 204 5232   719
154 0.025    0.54 0.7789816 0.7667439 0.370727968     1607 204 5234   719
155 0.025    0.55 0.7822319 0.7677743 0.286132032     1602 201 5239   722
156 0.025    0.56 0.7833153 0.7689335 0.287921178     1594 200 5247   723
157 0.025    0.57 0.7843987 0.7700927 0.289719023     1586 199 5255   724
158 0.025    0.58 0.7865655 0.7713807 0.259081852     1578 197 5263   726
159 0.025    0.59 0.7876490 0.7721535 0.248549676     1573 196 5268   727
160 0.025    0.60 0.7876490 0.7727975 0.269034296     1568 196 5273   727
161 0.025    0.61 0.7876490 0.7736991 0.299686605     1561 196 5280   727
162 0.025    0.62 0.7876490 0.7749871 0.347536594     1551 196 5290   727
163 0.025    0.63 0.7876490 0.7761463 0.394716844     1542 196 5299   727
164 0.025    0.64 0.7876490 0.7769191 0.428323805     1536 196 5305   727
165 0.025    0.65 0.7887324 0.7780783 0.430909878     1528 195 5313   728
166 0.025    0.66 0.7908992 0.7791087 0.380154294     1522 193 5319   730
167 0.025    0.67 0.7919827 0.7796239 0.356155270     1519 192 5322   731
168 0.025    0.68 0.7919827 0.7803967 0.387883828     1513 192 5328   731
169 0.025    0.69 0.7930661 0.7818135 0.401272598     1503 191 5338   732
170 0.025    0.70 0.7941495 0.7821999 0.371030855     1501 190 5340   733
171 0.025    0.71 0.7941495 0.7827151 0.392619998     1497 190 5344   733
172 0.025    0.72 0.7941495 0.7831015 0.409325611     1494 190 5347   733
173 0.025    0.73 0.7941495 0.7842607 0.462051905     1485 190 5356   733
174 0.025    0.74 0.7941495 0.7852911 0.512124031     1477 190 5364   733
175 0.025    0.75 0.7941495 0.7864503 0.571885571     1468 190 5373   733
176 0.025    0.76 0.7941495 0.7883823 0.678826047     1453 190 5388   733
177 0.025    0.77 0.7941495 0.7892839 0.731478126     1446 190 5395   733
178 0.025    0.78 0.7963164 0.7904431 0.671574812     1439 188 5402   735
179 0.025    0.79 0.7973998 0.7916023 0.675350781     1431 187 5410   736
180 0.025    0.80 0.7984832 0.7931479 0.701691804     1420 186 5421   737
181 0.025    0.81 0.7995666 0.7944359 0.713216303     1411 185 5430   738
182 0.025    0.82 0.7995666 0.7953375 0.767373192     1404 185 5437   738
183 0.025    0.83 0.8006501 0.7962391 0.755870004     1398 184 5443   739
184 0.025    0.84 0.8006501 0.7972694 0.819222965     1390 184 5451   739
185 0.025    0.85 0.8006501 0.7977846 0.851467576     1386 184 5455   739
186 0.025    0.86 0.8039003 0.7994590 0.752601626     1376 181 5465   742
187 0.025    0.87 0.8060672 0.8007470 0.698619380     1368 179 5473   744
188 0.025    0.88 0.8104009 0.8015198 0.498593768     1366 175 5475   748
189 0.025    0.89 0.8136511 0.8029366 0.407832240     1358 172 5483   751
190 0.025    0.90 0.8147346 0.8037094 0.392963632     1353 171 5488   752
191 0.025    0.91 0.8169014 0.8048686 0.348005229     1346 169 5495   754
192 0.025    0.92 0.8212351 0.8080886 0.300225107     1325 165 5516   758
193 0.025    0.93 0.8212351 0.8102782 0.389923710     1308 165 5533   758
194 0.025    0.94 0.8234020 0.8129830 0.412297595     1289 163 5552   760
195 0.025    0.95 0.8244854 0.8162030 0.517738004     1265 162 5576   761
196 0.025    0.96 0.8266522 0.8201958 0.618135590     1236 160 5605   763
197 0.025    0.97 0.8320693 0.8247038 0.561327985     1206 155 5635   768
198 0.025    0.98 0.8396533 0.8297269 0.419037165     1174 148 5667   775
199 0.025    0.99 0.8472373 0.8362957 0.362978439     1130 141 5711   782
200 0.025    1.00 1.0000000 1.0000000 0.000000000        0   0 6841   923
201 0.050    0.01 0.6952177 0.6813498 0.230574288     2047 427 4316   974
202 0.050    0.02 0.7059243 0.6926842 0.248292085     1974 412 4389   989
203 0.050    0.03 0.7109208 0.6971922 0.228877153     1946 405 4417   996
204 0.050    0.04 0.7159172 0.7028594 0.250520797     1909 398 4454  1003
205 0.050    0.05 0.7194861 0.7064657 0.250241749     1886 393 4477  1008
206 0.050    0.06 0.7237687 0.7102009 0.228591319     1863 387 4500  1014
207 0.050    0.07 0.7266238 0.7122617 0.200863880     1851 383 4512  1018
208 0.050    0.08 0.7273376 0.7145801 0.256254166     1834 382 4529  1019
209 0.050    0.09 0.7301927 0.7172849 0.249175189     1817 378 4546  1023
210 0.050    0.10 0.7316203 0.7206337 0.327329975     1793 376 4570  1025
211 0.050    0.11 0.7344754 0.7217929 0.255442043     1788 372 4575  1029
212 0.050    0.12 0.7359029 0.7237249 0.274379477     1775 370 4588  1031
213 0.050    0.13 0.7366167 0.7252705 0.308731593     1764 369 4599  1032
214 0.050    0.14 0.7387580 0.7269449 0.287709943     1754 366 4609  1035
215 0.050    0.15 0.7437545 0.7299073 0.209039610     1738 359 4625  1042
216 0.050    0.16 0.7458958 0.7314529 0.188824794     1729 356 4634  1045
217 0.050    0.17 0.7487509 0.7344152 0.190649439     1710 352 4653  1049
218 0.050    0.18 0.7487509 0.7349304 0.207232983     1706 352 4657  1049
219 0.050    0.19 0.7508922 0.7362184 0.179193958     1699 349 4664  1052
220 0.050    0.20 0.7530335 0.7373776 0.150598743     1693 346 4670  1055
221 0.050    0.21 0.7551749 0.7382792 0.119797961     1689 343 4674  1058
222 0.050    0.22 0.7551749 0.7390520 0.137715829     1683 343 4680  1058
223 0.050    0.23 0.7573162 0.7402112 0.114314513     1677 340 4686  1061
224 0.050    0.24 0.7587438 0.7411128 0.102990705     1672 338 4691  1063
225 0.050    0.25 0.7587438 0.7422720 0.127675645     1663 338 4700  1063
226 0.050    0.26 0.7587438 0.7434312 0.156822782     1654 338 4709  1063
227 0.050    0.27 0.7601713 0.7452344 0.166518940     1642 336 4721  1065
228 0.050    0.28 0.7615989 0.7465224 0.161796811     1634 334 4729  1067
229 0.050    0.29 0.7623126 0.7471664 0.159466378     1630 333 4733  1068
230 0.050    0.30 0.7630264 0.7479392 0.160713725     1625 332 4738  1069
231 0.050    0.31 0.7637402 0.7489696 0.169319717     1618 331 4745  1070
232 0.050    0.32 0.7665953 0.7506440 0.136146269     1609 327 4754  1074
233 0.050    0.33 0.7665953 0.7510304 0.145912175     1606 327 4757  1074
234 0.050    0.34 0.7673091 0.7520608 0.153918277     1599 326 4764  1075
235 0.050    0.35 0.7680228 0.7528336 0.155123816     1594 325 4769  1076
236 0.050    0.36 0.7680228 0.7536064 0.177333196     1588 325 4775  1076
237 0.050    0.37 0.7687366 0.7545080 0.182651524     1582 324 4781  1077
238 0.050    0.38 0.7708779 0.7552808 0.142738973     1579 321 4784  1080
239 0.050    0.39 0.7708779 0.7559248 0.160025648     1574 321 4789  1080
240 0.050    0.40 0.7708779 0.7563112 0.171147430     1571 321 4792  1080
241 0.050    0.41 0.7715917 0.7572128 0.176331524     1565 320 4798  1081
242 0.050    0.42 0.7751606 0.7587584 0.120995747     1558 315 4805  1086
243 0.050    0.43 0.7758744 0.7599176 0.131032034     1550 314 4813  1087
244 0.050    0.44 0.7765882 0.7604328 0.125919878     1547 313 4816  1088
245 0.050    0.45 0.7765882 0.7608192 0.135231260     1544 313 4819  1088
246 0.050    0.46 0.7765882 0.7609480 0.138452853     1543 313 4820  1088
247 0.050    0.47 0.7780157 0.7614632 0.116139852     1541 311 4822  1090
248 0.050    0.48 0.7794433 0.7630088 0.117999752     1531 309 4832  1092
249 0.050    0.49 0.7794433 0.7636528 0.133092427     1526 309 4837  1092
250 0.050    0.50 0.7801570 0.7642968 0.130984198     1522 308 4841  1093
251 0.050    0.51 0.7822984 0.7649408 0.097386027     1520 305 4843  1096
252 0.050    0.52 0.7822984 0.7653272 0.105037310     1517 305 4846  1096
253 0.050    0.53 0.7822984 0.7664863 0.130938718     1508 305 4855  1096
254 0.050    0.54 0.7830121 0.7667439 0.119805834     1507 304 4856  1097
255 0.050    0.55 0.7851535 0.7677743 0.095560323     1502 301 4861  1100
256 0.050    0.56 0.7865810 0.7689335 0.089884489     1495 299 4868  1102
257 0.050    0.57 0.7872948 0.7700927 0.097877891     1487 298 4876  1103
258 0.050    0.58 0.7887223 0.7713807 0.094477091     1479 296 4884  1105
259 0.050    0.59 0.7901499 0.7721535 0.082074224     1475 294 4888  1107
260 0.050    0.60 0.7908637 0.7727975 0.080568388     1471 293 4892  1108
261 0.050    0.61 0.7908637 0.7736991 0.096760127     1464 293 4899  1108
262 0.050    0.62 0.7908637 0.7749871 0.124390135     1454 293 4909  1108
263 0.050    0.63 0.7908637 0.7761463 0.154317933     1445 293 4918  1108
264 0.050    0.64 0.7908637 0.7769191 0.177192586     1439 293 4924  1108
265 0.050    0.65 0.7915774 0.7780783 0.190994672     1431 292 4932  1109
266 0.050    0.66 0.7930050 0.7791087 0.177207217     1425 290 4938  1111
267 0.050    0.67 0.7937188 0.7796239 0.170580228     1422 289 4941  1112
268 0.050    0.68 0.7937188 0.7803967 0.195358738     1416 289 4947  1112
269 0.050    0.69 0.7944325 0.7818135 0.219623152     1406 288 4957  1113
270 0.050    0.70 0.7958601 0.7821999 0.182660064     1405 286 4958  1115
271 0.050    0.71 0.7965739 0.7827151 0.175845583     1402 285 4961  1116
272 0.050    0.72 0.7965739 0.7831015 0.188253053     1399 285 4964  1116
273 0.050    0.73 0.7972877 0.7842607 0.202823843     1391 284 4972  1117
274 0.050    0.74 0.7972877 0.7852911 0.241192935     1383 284 4980  1117
275 0.050    0.75 0.7972877 0.7864503 0.290342826     1374 284 4989  1117
276 0.050    0.76 0.7987152 0.7883823 0.312580907     1361 282 5002  1119
277 0.050    0.77 0.7987152 0.7892839 0.357575603     1354 282 5009  1119
278 0.050    0.78 0.8001428 0.7904431 0.342559217     1347 280 5016  1121
279 0.050    0.79 0.8008565 0.7916023 0.365085335     1339 279 5024  1122
280 0.050    0.80 0.8015703 0.7931479 0.410337375     1328 278 5035  1123
281 0.050    0.81 0.8022841 0.7944359 0.443405150     1319 277 5044  1124
282 0.050    0.82 0.8022841 0.7953375 0.499477783     1312 277 5051  1124
283 0.050    0.83 0.8037116 0.7962391 0.465140384     1307 275 5056  1126
284 0.050    0.84 0.8044254 0.7972694 0.484409908     1300 274 5063  1127
285 0.050    0.85 0.8044254 0.7977846 0.517724255     1296 274 5067  1127
286 0.050    0.86 0.8065667 0.7994590 0.485748335     1286 271 5077  1130
287 0.050    0.87 0.8087081 0.8007470 0.431222264     1279 268 5084  1133
288 0.050    0.88 0.8115632 0.8015198 0.315327435     1277 264 5086  1137
289 0.050    0.89 0.8144183 0.8029366 0.247550655     1270 260 5093  1141
290 0.050    0.90 0.8165596 0.8037094 0.193431829     1267 257 5096  1144
291 0.050    0.91 0.8179872 0.8048686 0.183054664     1260 255 5103  1146
292 0.050    0.92 0.8215560 0.8080886 0.168671774     1240 250 5123  1151
293 0.050    0.93 0.8215560 0.8102782 0.249470873     1223 250 5140  1151
294 0.050    0.94 0.8236974 0.8129830 0.272092937     1205 247 5158  1154
295 0.050    0.95 0.8251249 0.8162030 0.360555954     1182 245 5181  1156
296 0.050    0.96 0.8265525 0.8201958 0.518302129     1153 243 5210  1158
297 0.050    0.97 0.8301213 0.8247038 0.582108356     1123 238 5240  1163
298 0.050    0.98 0.8372591 0.8297269 0.429951212     1094 228 5269  1173
299 0.050    0.99 0.8451106 0.8362957 0.344594448     1054 217 5309  1184
300 0.050    1.00 1.0000000 1.0000000 0.000000000        0   0 6363  1401
301 0.075    0.01 0.6919592 0.6813498 0.289332319     1930 544 4068  1222
302 0.075    0.02 0.7032843 0.6926842 0.285016018     1862 524 4136  1242
303 0.075    0.03 0.7072480 0.6971922 0.309187143     1834 517 4164  1249
304 0.075    0.04 0.7129105 0.7028594 0.306806665     1800 507 4198  1259
305 0.075    0.05 0.7157418 0.7064657 0.345070928     1777 502 4221  1264
306 0.075    0.06 0.7197055 0.7102009 0.331127491     1755 495 4243  1271
307 0.075    0.07 0.7231031 0.7122617 0.264815502     1745 489 4253  1277
308 0.075    0.08 0.7236693 0.7145801 0.351188429     1728 488 4270  1278
309 0.075    0.09 0.7270668 0.7172849 0.313206914     1713 482 4285  1284
310 0.075    0.10 0.7287656 0.7206337 0.402954625     1690 479 4308  1287
311 0.075    0.11 0.7310306 0.7217929 0.339371493     1685 475 4313  1291
312 0.075    0.12 0.7321631 0.7237249 0.383220990     1672 473 4326  1293
313 0.075    0.13 0.7327293 0.7252705 0.442133176     1661 472 4337  1294
314 0.075    0.14 0.7349943 0.7269449 0.404595624     1652 468 4346  1298
315 0.075    0.15 0.7389581 0.7299073 0.345104512     1636 461 4362  1305
316 0.075    0.16 0.7412231 0.7314529 0.306096113     1628 457 4370  1309
317 0.075    0.17 0.7440544 0.7344152 0.311124198     1610 452 4388  1314
318 0.075    0.18 0.7446206 0.7349304 0.308191229     1607 451 4391  1315
319 0.075    0.19 0.7468856 0.7362184 0.259904794     1601 447 4397  1319
320 0.075    0.20 0.7491506 0.7373776 0.211900491     1596 443 4402  1323
321 0.075    0.21 0.7508494 0.7382792 0.181403137     1592 440 4406  1326
322 0.075    0.22 0.7519819 0.7390520 0.168547194     1588 438 4410  1328
323 0.075    0.23 0.7542469 0.7402112 0.133759232     1583 434 4415  1332
324 0.075    0.24 0.7559456 0.7411128 0.112252800     1579 431 4419  1335
325 0.075    0.25 0.7559456 0.7422720 0.143260336     1570 431 4428  1335
326 0.075    0.26 0.7559456 0.7434312 0.180566278     1561 431 4437  1335
327 0.075    0.27 0.7576444 0.7452344 0.183301851     1550 428 4448  1338
328 0.075    0.28 0.7587769 0.7465224 0.188243940     1542 426 4456  1340
329 0.075    0.29 0.7593431 0.7471664 0.190755939     1538 425 4460  1341
330 0.075    0.30 0.7604757 0.7479392 0.177246313     1534 423 4464  1343
331 0.075    0.31 0.7610419 0.7489696 0.193621857     1527 422 4471  1344
332 0.075    0.32 0.7638732 0.7506440 0.152519807     1519 417 4479  1349
333 0.075    0.33 0.7638732 0.7510304 0.164922416     1516 417 4482  1349
334 0.075    0.34 0.7655719 0.7520608 0.143020148     1511 414 4487  1352
335 0.075    0.35 0.7661382 0.7528336 0.148942196     1506 413 4492  1353
336 0.075    0.36 0.7661382 0.7536064 0.174130044     1500 413 4498  1353
337 0.075    0.37 0.7672707 0.7545080 0.165629772     1495 411 4503  1355
338 0.075    0.38 0.7689694 0.7552808 0.136004364     1492 408 4506  1358
339 0.075    0.39 0.7689694 0.7559248 0.155467148     1487 408 4511  1358
340 0.075    0.40 0.7689694 0.7563112 0.168137742     1484 408 4514  1358
341 0.075    0.41 0.7695357 0.7572128 0.179416962     1478 407 4520  1359
342 0.075    0.42 0.7729332 0.7587584 0.120559457     1472 401 4526  1365
343 0.075    0.43 0.7734994 0.7599176 0.136589189     1464 400 4534  1366
344 0.075    0.44 0.7746319 0.7604328 0.119029986     1462 398 4536  1368
345 0.075    0.45 0.7746319 0.7608192 0.129415051     1459 398 4539  1368
346 0.075    0.46 0.7746319 0.7609480 0.133031502     1458 398 4540  1368
347 0.075    0.47 0.7757644 0.7614632 0.115807148     1456 396 4542  1370
348 0.075    0.48 0.7774632 0.7630088 0.111079414     1447 393 4551  1373
349 0.075    0.49 0.7774632 0.7636528 0.127913827     1442 393 4556  1373
350 0.075    0.50 0.7780294 0.7642968 0.129757649     1438 392 4560  1374
351 0.075    0.51 0.7797282 0.7649408 0.101960699     1436 389 4562  1377
352 0.075    0.52 0.7797282 0.7653272 0.111213748     1433 389 4565  1377
353 0.075    0.53 0.7797282 0.7664863 0.143057866     1424 389 4574  1377
354 0.075    0.54 0.7802945 0.7667439 0.133625939     1423 388 4575  1378
355 0.075    0.55 0.7819932 0.7677743 0.114577379     1418 385 4580  1381
356 0.075    0.56 0.7836920 0.7689335 0.100608600     1412 382 4586  1384
357 0.075    0.57 0.7848245 0.7700927 0.100637291     1405 380 4593  1386
358 0.075    0.58 0.7859570 0.7713807 0.103670922     1397 378 4601  1388
359 0.075    0.59 0.7876557 0.7721535 0.082775926     1394 375 4604  1391
360 0.075    0.60 0.7882220 0.7727975 0.084048564     1390 374 4608  1392
361 0.075    0.61 0.7882220 0.7736991 0.103721480     1383 374 4615  1392
362 0.075    0.62 0.7882220 0.7749871 0.138101259     1373 374 4625  1392
363 0.075    0.63 0.7882220 0.7761463 0.176165025     1364 374 4634  1392
364 0.075    0.64 0.7887882 0.7769191 0.183319508     1359 373 4639  1393
365 0.075    0.65 0.7893545 0.7780783 0.205922976     1351 372 4647  1394
366 0.075    0.66 0.7904870 0.7791087 0.200991498     1345 370 4653  1396
367 0.075    0.67 0.7910532 0.7796239 0.198550751     1342 369 4656  1397
368 0.075    0.68 0.7916195 0.7803967 0.206424231     1337 368 4661  1398
369 0.075    0.69 0.7921857 0.7818135 0.242829301     1327 367 4671  1399
370 0.075    0.70 0.7933182 0.7821999 0.209436174     1326 365 4672  1401
371 0.075    0.71 0.7938845 0.7827151 0.206909321     1323 364 4675  1402
372 0.075    0.72 0.7938845 0.7831015 0.223187738     1320 364 4678  1402
373 0.075    0.73 0.7950170 0.7842607 0.223468125     1313 362 4685  1404
374 0.075    0.74 0.7950170 0.7852911 0.271551238     1305 362 4693  1404
375 0.075    0.75 0.7950170 0.7864503 0.333832026     1296 362 4702  1404
376 0.075    0.76 0.7961495 0.7883823 0.381002415     1283 360 4715  1406
377 0.075    0.77 0.7961495 0.7892839 0.440280432     1276 360 4722  1406
378 0.075    0.78 0.7972820 0.7904431 0.441212242     1269 358 4729  1408
379 0.075    0.79 0.7984145 0.7916023 0.442143372     1262 356 4736  1410
380 0.075    0.80 0.7989807 0.7931479 0.512408825     1251 355 4747  1411
381 0.075    0.81 0.7995470 0.7944359 0.567853179     1242 354 4756  1412
382 0.075    0.82 0.7995470 0.7953375 0.641713961     1235 354 4763  1412
383 0.075    0.83 0.8006795 0.7962391 0.621675892     1230 352 4768  1414
384 0.075    0.84 0.8018120 0.7972694 0.612469048     1224 350 4774  1416
385 0.075    0.85 0.8018120 0.7977846 0.655810207     1220 350 4778  1416
386 0.075    0.86 0.8035108 0.7994590 0.652709124     1210 347 4788  1419
387 0.075    0.87 0.8063420 0.8007470 0.524896953     1205 342 4793  1424
388 0.075    0.88 0.8086070 0.8015198 0.414718044     1203 338 4795  1428
389 0.075    0.89 0.8114383 0.8029366 0.323232770     1197 333 4801  1433
390 0.075    0.90 0.8131370 0.8037094 0.270998964     1194 330 4804  1436
391 0.075    0.91 0.8142695 0.8048686 0.271326032     1187 328 4811  1438
392 0.075    0.92 0.8176670 0.8080886 0.259090097     1168 322 4830  1444
393 0.075    0.93 0.8176670 0.8102782 0.386218009     1151 322 4847  1444
394 0.075    0.94 0.8193658 0.8129830 0.454503114     1133 319 4865  1447
395 0.075    0.95 0.8204983 0.8162030 0.620404912     1110 317 4888  1449
396 0.075    0.96 0.8227633 0.8201958 0.776093903     1083 313 4915  1453
397 0.075    0.97 0.8278596 0.8247038 0.717925349     1057 304 4941  1462
398 0.075    0.98 0.8352208 0.8297269 0.507445442     1031 291 4967  1475
399 0.075    0.99 0.8414496 0.8362957 0.529092534      991 280 5007  1486
400 0.075    1.00 1.0000000 1.0000000 0.000000000        0   0 5998  1766
401 0.100    0.01 0.6885797 0.6813498 0.423329736     1825 649 3855  1435
402 0.100    0.02 0.7005758 0.6926842 0.376076902     1762 624 3918  1460
403 0.100    0.03 0.7039347 0.6971922 0.450039310     1734 617 3946  1467
404 0.100    0.04 0.7111324 0.7028594 0.348148980     1705 602 3975  1482
405 0.100    0.05 0.7149712 0.7064657 0.332667303     1685 594 3995  1490
406 0.100    0.06 0.7188100 0.7102009 0.324821889     1664 586 4016  1498
407 0.100    0.07 0.7216891 0.7122617 0.278737882     1654 580 4026  1504
408 0.100    0.08 0.7226488 0.7145801 0.354856587     1638 578 4042  1506
409 0.100    0.09 0.7255278 0.7172849 0.342860790     1623 572 4057  1512
410 0.100    0.10 0.7274472 0.7206337 0.434246681     1601 568 4079  1516
411 0.100    0.11 0.7293666 0.7217929 0.382398766     1596 564 4084  1520
412 0.100    0.12 0.7308061 0.7237249 0.414166429     1584 561 4096  1523
413 0.100    0.13 0.7312860 0.7252705 0.489832662     1573 560 4107  1524
414 0.100    0.14 0.7332054 0.7269449 0.470761991     1564 556 4116  1528
415 0.100    0.15 0.7370441 0.7299073 0.407071753     1549 548 4131  1536
416 0.100    0.16 0.7389635 0.7314529 0.381261318     1541 544 4139  1540
417 0.100    0.17 0.7413628 0.7344152 0.417590051     1523 539 4157  1545
418 0.100    0.18 0.7418426 0.7349304 0.419760192     1520 538 4160  1546
419 0.100    0.19 0.7452015 0.7362184 0.289638908     1517 531 4163  1553
420 0.100    0.20 0.7476008 0.7373776 0.225967619     1513 526 4167  1558
421 0.100    0.21 0.7490403 0.7382792 0.201435961     1509 523 4171  1561
422 0.100    0.22 0.7500000 0.7390520 0.193119277     1505 521 4175  1563
423 0.100    0.23 0.7519194 0.7402112 0.162772136     1500 517 4180  1567
424 0.100    0.24 0.7533589 0.7411128 0.143485529     1496 514 4184  1570
425 0.100    0.25 0.7533589 0.7422720 0.185628741     1487 514 4193  1570
426 0.100    0.26 0.7533589 0.7434312 0.236447860     1478 514 4202  1570
427 0.100    0.27 0.7557582 0.7452344 0.207790258     1469 509 4211  1575
428 0.100    0.28 0.7567179 0.7465224 0.221900443     1461 507 4219  1577
429 0.100    0.29 0.7571977 0.7471664 0.229223980     1457 506 4223  1578
430 0.100    0.30 0.7581574 0.7479392 0.219990492     1453 504 4227  1580
431 0.100    0.31 0.7586372 0.7489696 0.245863506     1446 503 4234  1581
432 0.100    0.32 0.7610365 0.7506440 0.210400528     1438 498 4242  1586
433 0.100    0.33 0.7610365 0.7510304 0.228040714     1435 498 4245  1586
434 0.100    0.34 0.7624760 0.7520608 0.208512683     1430 495 4250  1589
435 0.100    0.35 0.7629559 0.7528336 0.221429079     1425 494 4255  1590
436 0.100    0.36 0.7629559 0.7536064 0.259190588     1419 494 4261  1590
437 0.100    0.37 0.7639155 0.7545080 0.255577851     1414 492 4266  1592
438 0.100    0.38 0.7658349 0.7552808 0.200383563     1412 488 4268  1596
439 0.100    0.39 0.7658349 0.7559248 0.229525902     1407 488 4273  1596
440 0.100    0.40 0.7658349 0.7563112 0.248423096     1404 488 4276  1596
441 0.100    0.41 0.7663148 0.7572128 0.269965751     1398 487 4282  1597
442 0.100    0.42 0.7691939 0.7587584 0.203410926     1392 481 4288  1603
443 0.100    0.43 0.7701536 0.7599176 0.211643607     1385 479 4295  1605
444 0.100    0.44 0.7711132 0.7604328 0.191702192     1383 477 4297  1607
445 0.100    0.45 0.7715931 0.7608192 0.187512271     1381 476 4299  1608
446 0.100    0.46 0.7715931 0.7609480 0.192882277     1380 476 4300  1608
447 0.100    0.47 0.7725528 0.7614632 0.174232456     1378 474 4302  1610
448 0.100    0.48 0.7744722 0.7630088 0.158927879     1370 470 4310  1614
449 0.100    0.49 0.7749520 0.7636528 0.164715067     1366 469 4314  1615
450 0.100    0.50 0.7759117 0.7642968 0.152603436     1363 467 4317  1617
451 0.100    0.51 0.7773512 0.7649408 0.125551063     1361 464 4319  1620
452 0.100    0.52 0.7773512 0.7653272 0.137783817     1358 464 4322  1620
453 0.100    0.53 0.7778311 0.7664863 0.161230829     1350 463 4330  1621
454 0.100    0.54 0.7783109 0.7667439 0.152851811     1349 462 4331  1622
455 0.100    0.55 0.7797505 0.7677743 0.137954308     1344 459 4336  1625
456 0.100    0.56 0.7816699 0.7689335 0.113580445     1339 455 4341  1629
457 0.100    0.57 0.7831094 0.7700927 0.105092224     1333 452 4347  1632
458 0.100    0.58 0.7845489 0.7713807 0.100359335     1326 449 4354  1635
459 0.100    0.59 0.7859885 0.7721535 0.083645521     1323 446 4357  1638
460 0.100    0.60 0.7864683 0.7727975 0.087130198     1319 445 4361  1639
461 0.100    0.61 0.7869482 0.7736991 0.097046432     1313 444 4367  1640
462 0.100    0.62 0.7874280 0.7749871 0.118898595     1304 443 4376  1641
463 0.100    0.63 0.7879079 0.7761463 0.140134546     1296 442 4384  1642
464 0.100    0.64 0.7883877 0.7769191 0.149994495     1291 441 4389  1643
465 0.100    0.65 0.7888676 0.7780783 0.175426042     1283 440 4397  1644
466 0.100    0.66 0.7898273 0.7791087 0.177614918     1277 438 4403  1646
467 0.100    0.67 0.7903071 0.7796239 0.178718257     1274 437 4406  1647
468 0.100    0.68 0.7907869 0.7803967 0.190656376     1269 436 4411  1648
469 0.100    0.69 0.7912668 0.7818135 0.233805574     1259 435 4421  1649
470 0.100    0.70 0.7922265 0.7821999 0.205689839     1258 433 4422  1651
471 0.100    0.71 0.7931862 0.7827151 0.185464783     1256 431 4424  1653
472 0.100    0.72 0.7931862 0.7831015 0.202334979     1253 431 4427  1653
473 0.100    0.73 0.7946257 0.7842607 0.188920732     1247 428 4433  1656
474 0.100    0.74 0.7946257 0.7852911 0.237153395     1239 428 4441  1656
475 0.100    0.75 0.7946257 0.7864503 0.301373473     1230 428 4450  1656
476 0.100    0.76 0.7955854 0.7883823 0.362887430     1217 426 4463  1658
477 0.100    0.77 0.7955854 0.7892839 0.427600017     1210 426 4470  1658
478 0.100    0.78 0.7965451 0.7904431 0.442041624     1203 424 4477  1660
479 0.100    0.79 0.7975048 0.7916023 0.456813217     1196 422 4484  1662
480 0.100    0.80 0.7979846 0.7931479 0.544700971     1185 421 4495  1663
481 0.100    0.81 0.7994242 0.7944359 0.530569889     1178 418 4502  1666
482 0.100    0.82 0.7999040 0.7953375 0.567073380     1172 417 4508  1667
483 0.100    0.83 0.8013436 0.7962391 0.519194507     1168 414 4512  1670
484 0.100    0.84 0.8027831 0.7972694 0.483851047     1163 411 4517  1673
485 0.100    0.85 0.8032630 0.7977846 0.486372853     1160 410 4520  1674
486 0.100    0.86 0.8051823 0.7994590 0.464832093     1151 406 4529  1678
487 0.100    0.87 0.8075816 0.8007470 0.378229103     1146 401 4534  1683
488 0.100    0.88 0.8095010 0.8015198 0.300257379     1144 397 4536  1687
489 0.100    0.89 0.8119002 0.8029366 0.241799718     1138 392 4542  1692
490 0.100    0.90 0.8133397 0.8037094 0.207009424     1135 389 4545  1695
491 0.100    0.91 0.8142994 0.8048686 0.215792496     1128 387 4552  1697
492 0.100    0.92 0.8171785 0.8080886 0.230356215     1109 381 4571  1703
493 0.100    0.93 0.8176583 0.8102782 0.331064989     1093 380 4587  1704
494 0.100    0.94 0.8195777 0.8129830 0.384388279     1076 376 4604  1708
495 0.100    0.95 0.8205374 0.8162030 0.572601497     1053 374 4627  1710
496 0.100    0.96 0.8238964 0.8201958 0.630538603     1029 367 4651  1717
497 0.100    0.97 0.8282150 0.8247038 0.646091356     1003 358 4677  1726
498 0.100    0.98 0.8349328 0.8297269 0.480718893      978 344 4702  1740
499 0.100    0.99 0.8416507 0.8362957 0.460618866      941 330 4739  1754
500 0.100    1.00 1.0000000 1.0000000 0.000000000        0   0 5680  2084
enrichment.plotter(gene.hic.filt, "weighted_Z.s2post.C", "adj.P.Val", "FDR for Weighted p-val Combine of Hi-C Contacts Overlapping Gene, Chimp")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR  prop.obs  prop.exp    chisq.p Dneither  DE DHiC Dboth
1   0.010    0.01 0.7089716 0.6751510 0.12361082     2394 133 4928   324
2   0.010    0.02 0.7221007 0.6855637 0.09255552     2319 127 5003   330
3   0.010    0.03 0.7242888 0.6898059 0.11172806     2287 126 5035   331
4   0.010    0.04 0.7308534 0.6949479 0.09572256     2250 123 5072   334
5   0.010    0.05 0.7352298 0.6986759 0.08858915     2223 121 5099   336
6   0.010    0.06 0.7374179 0.7018897 0.09717341     2199 120 5123   337
7   0.010    0.07 0.7439825 0.7040751 0.06098030     2185 117 5137   340
8   0.010    0.08 0.7461707 0.7063890 0.06122877     2168 116 5154   341
9   0.010    0.09 0.7461707 0.7085744 0.07673085     2151 116 5171   341
10  0.010    0.10 0.7461707 0.7119167 0.10665563     2125 116 5197   341
11  0.010    0.11 0.7483589 0.7129451 0.09459925     2118 115 5204   342
12  0.010    0.12 0.7505470 0.7146163 0.08917371     2106 114 5216   343
13  0.010    0.13 0.7505470 0.7162874 0.10499692     2093 114 5229   343
14  0.010    0.14 0.7505470 0.7180872 0.12451738     2079 114 5243   343
15  0.010    0.15 0.7527352 0.7213009 0.13594355     2055 113 5267   344
16  0.010    0.16 0.7549234 0.7232292 0.13179570     2041 112 5281   345
17  0.010    0.17 0.7571116 0.7254146 0.13081349     2025 111 5297   346
18  0.010    0.18 0.7571116 0.7261859 0.14045174     2019 111 5303   346
19  0.010    0.19 0.7592998 0.7273428 0.12674004     2011 110 5311   347
20  0.010    0.20 0.7614880 0.7279856 0.10855188     2007 109 5315   348
21  0.010    0.21 0.7636761 0.7288855 0.09486715     2001 108 5321   349
22  0.010    0.22 0.7636761 0.7295282 0.10108278     1996 108 5326   349
23  0.010    0.23 0.7636761 0.7306852 0.11310836     1987 108 5335   349
24  0.010    0.24 0.7658643 0.7319707 0.10274689     1978 107 5344   350
25  0.010    0.25 0.7658643 0.7336419 0.12075207     1965 107 5357   350
26  0.010    0.26 0.7658643 0.7353130 0.14121622     1952 107 5370   350
27  0.010    0.27 0.7680525 0.7373698 0.13846190     1937 106 5385   351
28  0.010    0.28 0.7724289 0.7383983 0.09868395     1931 104 5391   353
29  0.010    0.29 0.7724289 0.7394267 0.10921155     1923 104 5399   353
30  0.010    0.30 0.7724289 0.7403265 0.11915691     1916 104 5406   353
31  0.010    0.31 0.7724289 0.7414835 0.13300449     1907 104 5415   353
32  0.010    0.32 0.7724289 0.7432832 0.15706666     1893 104 5429   353
33  0.010    0.33 0.7724289 0.7436689 0.16264224     1890 104 5432   353
34  0.010    0.34 0.7724289 0.7444402 0.17425559     1884 104 5438   353
35  0.010    0.35 0.7724289 0.7454686 0.19072519     1876 104 5446   353
36  0.010    0.36 0.7746171 0.7463684 0.16906596     1870 103 5452   354
37  0.010    0.37 0.7768053 0.7473968 0.15103825     1863 102 5459   355
38  0.010    0.38 0.7789934 0.7480396 0.12963973     1859 101 5463   356
39  0.010    0.39 0.7789934 0.7486823 0.13776681     1854 101 5468   356
40  0.010    0.40 0.7789934 0.7490680 0.14283471     1851 101 5471   356
41  0.010    0.41 0.7811816 0.7497108 0.12230304     1847 100 5475   357
42  0.010    0.42 0.7833698 0.7512534 0.11381483     1836  99 5486   358
43  0.010    0.43 0.7855580 0.7521532 0.09915889     1830  98 5492   359
44  0.010    0.44 0.7855580 0.7526674 0.10441123     1826  98 5496   359
45  0.010    0.45 0.7855580 0.7531816 0.10988927     1822  98 5500   359
46  0.010    0.46 0.7855580 0.7533102 0.11129479     1821  98 5501   359
47  0.010    0.47 0.7877462 0.7539530 0.09435448     1817  97 5505   360
48  0.010    0.48 0.7899344 0.7553670 0.08619879     1807  96 5515   361
49  0.010    0.49 0.7899344 0.7563954 0.09582150     1799  96 5523   361
50  0.010    0.50 0.7921225 0.7571667 0.08184848     1794  95 5528   362
51  0.010    0.51 0.7943107 0.7579380 0.06954985     1789  94 5533   363
52  0.010    0.52 0.7943107 0.7585808 0.07452442     1784  94 5538   363
53  0.010    0.53 0.7943107 0.7598663 0.08537372     1774  94 5548   363
54  0.010    0.54 0.7943107 0.7606376 0.09249357     1768  94 5554   363
55  0.010    0.55 0.7986871 0.7616660 0.06316611     1762  92 5560   365
56  0.010    0.56 0.7986871 0.7623088 0.06777884     1757  92 5565   365
57  0.010    0.57 0.8008753 0.7633372 0.05884761     1750  91 5572   366
58  0.010    0.58 0.8008753 0.7643656 0.06594766     1742  91 5580   366
59  0.010    0.59 0.8008753 0.7652655 0.07274389     1735  91 5587   366
60  0.010    0.60 0.8008753 0.7657797 0.07688613     1731  91 5591   366
61  0.010    0.61 0.8008753 0.7666795 0.08461165     1724  91 5598   366
62  0.010    0.62 0.8008753 0.7678365 0.09548620     1715  91 5607   366
63  0.010    0.63 0.8008753 0.7686078 0.10335961     1709  91 5613   366
64  0.010    0.64 0.8030635 0.7695076 0.08943089     1703  90 5619   367
65  0.010    0.65 0.8030635 0.7707932 0.10218492     1693  90 5629   367
66  0.010    0.66 0.8030635 0.7715645 0.11053160     1687  90 5635   367
67  0.010    0.67 0.8074398 0.7720787 0.07186967     1685  88 5637   369
68  0.010    0.68 0.8074398 0.7728500 0.07814817     1679  88 5643   369
69  0.010    0.69 0.8074398 0.7740069 0.08842556     1670  88 5652   369
70  0.010    0.70 0.8096280 0.7745211 0.07290871     1667  87 5655   370
71  0.010    0.71 0.8096280 0.7749068 0.07603936     1664  87 5658   370
72  0.010    0.72 0.8096280 0.7752925 0.07928245     1661  87 5661   370
73  0.010    0.73 0.8096280 0.7765780 0.09094264     1651  87 5671   370
74  0.010    0.74 0.8096280 0.7770922 0.09599032     1647  87 5675   370
75  0.010    0.75 0.8096280 0.7783777 0.10963103     1637  87 5685   370
76  0.010    0.76 0.8096280 0.7799203 0.12805462     1625  87 5697   370
77  0.010    0.77 0.8096280 0.7806916 0.13816345     1619  87 5703   370
78  0.010    0.78 0.8096280 0.7817200 0.15262581     1611  87 5711   370
79  0.010    0.79 0.8096280 0.7827484 0.16826329     1603  87 5719   370
80  0.010    0.80 0.8140044 0.7841625 0.12362738     1594  85 5728   372
81  0.010    0.81 0.8161926 0.7857051 0.11447236     1583  84 5739   373
82  0.010    0.82 0.8161926 0.7866050 0.12541647     1576  84 5746   373
83  0.010    0.83 0.8161926 0.7878905 0.14250608     1566  84 5756   373
84  0.010    0.84 0.8161926 0.7885332 0.15172436     1561  84 5761   373
85  0.010    0.85 0.8161926 0.7891760 0.16141034     1556  84 5766   373
86  0.010    0.86 0.8183807 0.7907186 0.15012449     1545  83 5777   374
87  0.010    0.87 0.8183807 0.7926469 0.18050419     1530  83 5792   374
88  0.010    0.88 0.8249453 0.7943180 0.10740274     1520  80 5802   377
89  0.010    0.89 0.8271335 0.7959892 0.10035589     1508  79 5814   378
90  0.010    0.90 0.8293217 0.7963749 0.08134783     1506  78 5816   379
91  0.010    0.91 0.8293217 0.7975318 0.09233990     1497  78 5825   379
92  0.010    0.92 0.8358862 0.8001028 0.05596867     1480  75 5842   382
93  0.010    0.93 0.8358862 0.8025453 0.07427123     1461  75 5861   382
94  0.010    0.94 0.8424508 0.8051163 0.04380494     1444  72 5878   385
95  0.010    0.95 0.8424508 0.8082016 0.06351742     1420  72 5902   385
96  0.010    0.96 0.8468271 0.8119296 0.05663638     1393  70 5929   387
97  0.010    0.97 0.8555799 0.8175858 0.03525628     1353  66 5969   391
98  0.010    0.98 0.8621444 0.8227279 0.02702824     1316  63 6006   394
99  0.010    0.99 0.8730853 0.8295411 0.01286596     1268  58 6054   399
100 0.010    1.00 1.0000000 1.0000000 0.00000000        0   0 7322   457
101 0.025    0.01 0.6880435 0.6751510 0.39435051     2240 287 4619   633
102 0.025    0.02 0.7010870 0.6855637 0.29733059     2171 275 4688   645
103 0.025    0.03 0.7054348 0.6898059 0.29214751     2142 271 4717   649
104 0.025    0.04 0.7130435 0.6949479 0.21818251     2109 264 4750   656
105 0.025    0.05 0.7195652 0.6986759 0.15204692     2086 258 4773   662
106 0.025    0.06 0.7217391 0.7018897 0.17278581     2063 256 4796   664
107 0.025    0.07 0.7250000 0.7040751 0.14921348     2049 253 4810   667
108 0.025    0.08 0.7282609 0.7063890 0.13033584     2034 250 4825   670
109 0.025    0.09 0.7304348 0.7085744 0.12970087     2019 248 4840   672
110 0.025    0.10 0.7304348 0.7119167 0.19981872     1993 248 4866   672
111 0.025    0.11 0.7326087 0.7129451 0.17218135     1987 246 4872   674
112 0.025    0.12 0.7347826 0.7146163 0.16044454     1976 244 4883   676
113 0.025    0.13 0.7358696 0.7162874 0.17250416     1964 243 4895   677
114 0.025    0.14 0.7369565 0.7180872 0.18828748     1951 242 4908   678
115 0.025    0.15 0.7402174 0.7213009 0.18561353     1929 239 4930   681
116 0.025    0.16 0.7413043 0.7232292 0.20560003     1915 238 4944   682
117 0.025    0.17 0.7423913 0.7254146 0.23429414     1899 237 4960   683
118 0.025    0.18 0.7423913 0.7261859 0.25656881     1893 237 4966   683
119 0.025    0.19 0.7434783 0.7273428 0.25807174     1885 236 4974   684
120 0.025    0.20 0.7445652 0.7279856 0.24440790     1881 235 4978   685
121 0.025    0.21 0.7456522 0.7288855 0.23845980     1875 234 4984   686
122 0.025    0.22 0.7456522 0.7295282 0.25722055     1870 234 4989   686
123 0.025    0.23 0.7467391 0.7306852 0.25872101     1862 233 4997   687
124 0.025    0.24 0.7500000 0.7319707 0.20224325     1855 230 5004   690
125 0.025    0.25 0.7500000 0.7336419 0.24784172     1842 230 5017   690
126 0.025    0.26 0.7500000 0.7353130 0.30040235     1829 230 5030   690
127 0.025    0.27 0.7510870 0.7373698 0.33355560     1814 229 5045   691
128 0.025    0.28 0.7532609 0.7383983 0.29262070     1808 227 5051   693
129 0.025    0.29 0.7543478 0.7394267 0.29003746     1801 226 5058   694
130 0.025    0.30 0.7565217 0.7403265 0.24887412     1796 224 5063   696
131 0.025    0.31 0.7576087 0.7414835 0.25030909     1788 223 5071   697
132 0.025    0.32 0.7586957 0.7432832 0.27154241     1775 222 5084   698
133 0.025    0.33 0.7586957 0.7436689 0.28393257     1772 222 5087   698
134 0.025    0.34 0.7586957 0.7444402 0.30988366     1766 222 5093   698
135 0.025    0.35 0.7586957 0.7454686 0.34693459     1758 222 5101   698
136 0.025    0.36 0.7597826 0.7463684 0.33930414     1752 221 5107   699
137 0.025    0.37 0.7608696 0.7473968 0.33646282     1745 220 5114   700
138 0.025    0.38 0.7619565 0.7480396 0.31971696     1741 219 5118   701
139 0.025    0.39 0.7619565 0.7486823 0.34311964     1736 219 5123   701
140 0.025    0.40 0.7619565 0.7490680 0.35769295     1733 219 5126   701
141 0.025    0.41 0.7630435 0.7497108 0.34024619     1729 218 5130   702
142 0.025    0.42 0.7663043 0.7512534 0.27834628     1720 215 5139   705
143 0.025    0.43 0.7673913 0.7521532 0.27161302     1714 214 5145   706
144 0.025    0.44 0.7684783 0.7526674 0.25303808     1711 213 5148   707
145 0.025    0.45 0.7684783 0.7531816 0.26903944     1707 213 5152   707
146 0.025    0.46 0.7684783 0.7533102 0.27314948     1706 213 5153   707
147 0.025    0.47 0.7695652 0.7539530 0.25842788     1702 212 5157   708
148 0.025    0.48 0.7706522 0.7553670 0.26797624     1692 211 5167   709
149 0.025    0.49 0.7706522 0.7563954 0.30210593     1684 211 5175   709
150 0.025    0.50 0.7717391 0.7571667 0.29059508     1679 210 5180   710
151 0.025    0.51 0.7739130 0.7579380 0.24453134     1675 208 5184   712
152 0.025    0.52 0.7739130 0.7585808 0.26430505     1670 208 5189   712
153 0.025    0.53 0.7739130 0.7598663 0.30720644     1660 208 5199   712
154 0.025    0.54 0.7739130 0.7606376 0.33512775     1654 208 5205   712
155 0.025    0.55 0.7760870 0.7616660 0.29275043     1648 206 5211   714
156 0.025    0.56 0.7771739 0.7623088 0.27712860     1644 205 5215   715
157 0.025    0.57 0.7782609 0.7633372 0.27445238     1637 204 5222   716
158 0.025    0.58 0.7793478 0.7643656 0.27178205     1630 203 5229   717
159 0.025    0.59 0.7804348 0.7652655 0.26498578     1624 202 5235   718
160 0.025    0.60 0.7804348 0.7657797 0.28178716     1620 202 5239   718
161 0.025    0.61 0.7815217 0.7666795 0.27481416     1614 201 5245   719
162 0.025    0.62 0.7815217 0.7678365 0.31469393     1605 201 5254   719
163 0.025    0.63 0.7815217 0.7686078 0.34337778     1599 201 5260   719
164 0.025    0.64 0.7826087 0.7695076 0.33546970     1593 200 5266   720
165 0.025    0.65 0.7836957 0.7707932 0.34222022     1584 199 5275   721
166 0.025    0.66 0.7847826 0.7715645 0.32946089     1579 198 5280   722
167 0.025    0.67 0.7869565 0.7720787 0.26969053     1577 196 5282   724
168 0.025    0.68 0.7880435 0.7728500 0.25871617     1572 195 5287   725
169 0.025    0.69 0.7891304 0.7740069 0.26013809     1564 194 5295   726
170 0.025    0.70 0.7902174 0.7745211 0.24150028     1561 193 5298   727
171 0.025    0.71 0.7902174 0.7749068 0.25340051     1558 193 5301   727
172 0.025    0.72 0.7902174 0.7752925 0.26571770     1555 193 5304   727
173 0.025    0.73 0.7902174 0.7765780 0.30983765     1545 193 5314   727
174 0.025    0.74 0.7902174 0.7770922 0.32882233     1541 193 5318   727
175 0.025    0.75 0.7902174 0.7783777 0.37965575     1531 193 5328   727
176 0.025    0.76 0.7902174 0.7799203 0.44698018     1519 193 5340   727
177 0.025    0.77 0.7902174 0.7806916 0.48317416     1513 193 5346   727
178 0.025    0.78 0.7913043 0.7817200 0.47958380     1506 192 5353   728
179 0.025    0.79 0.7913043 0.7827484 0.53025188     1498 192 5361   728
180 0.025    0.80 0.7945652 0.7841625 0.43886562     1490 189 5369   731
181 0.025    0.81 0.7956522 0.7857051 0.45914307     1479 188 5380   732
182 0.025    0.82 0.7956522 0.7866050 0.50257279     1472 188 5387   732
183 0.025    0.83 0.7967391 0.7878905 0.51167105     1463 187 5396   733
184 0.025    0.84 0.7967391 0.7885332 0.54443343     1458 187 5401   733
185 0.025    0.85 0.7967391 0.7891760 0.57828082     1453 187 5406   733
186 0.025    0.86 0.8000000 0.7907186 0.48778470     1444 184 5415   736
187 0.025    0.87 0.8010870 0.7926469 0.52923509     1430 183 5429   737
188 0.025    0.88 0.8076087 0.7943180 0.30834770     1423 177 5436   743
189 0.025    0.89 0.8119565 0.7959892 0.21633234     1414 173 5445   747
190 0.025    0.90 0.8130435 0.7963749 0.19585042     1412 172 5447   748
191 0.025    0.91 0.8152174 0.7975318 0.16821532     1405 170 5454   750
192 0.025    0.92 0.8195652 0.8001028 0.12649361     1389 166 5470   754
193 0.025    0.93 0.8195652 0.8025453 0.18123423     1370 166 5489   754
194 0.025    0.94 0.8239130 0.8051163 0.13661984     1354 162 5505   758
195 0.025    0.95 0.8250000 0.8082016 0.18233179     1331 161 5528   759
196 0.025    0.96 0.8304348 0.8119296 0.13760891     1307 156 5552   764
197 0.025    0.97 0.8380435 0.8175858 0.09577676     1270 149 5589   771
198 0.025    0.98 0.8434783 0.8227279 0.08742527     1235 144 5624   776
199 0.025    0.99 0.8532609 0.8295411 0.04649612     1191 135 5668   785
200 0.025    1.00 1.0000000 1.0000000 0.00000000        0   0 6859   920
201 0.050    0.01 0.6864710 0.6751510 0.33409404     2089 438 4293   959
202 0.050    0.02 0.6979241 0.6855637 0.28608353     2024 422 4358   975
203 0.050    0.03 0.7029349 0.6898059 0.25458853     1998 415 4384   982
204 0.050    0.04 0.7086614 0.6949479 0.23132066     1966 407 4416   990
205 0.050    0.05 0.7129563 0.6986759 0.21052798     1943 401 4439   996
206 0.050    0.06 0.7158196 0.7018897 0.22082336     1922 397 4460  1000
207 0.050    0.07 0.7186829 0.7040751 0.19766582     1909 393 4473  1004
208 0.050    0.08 0.7208304 0.7063890 0.20192250     1894 390 4488  1007
209 0.050    0.09 0.7222620 0.7085744 0.22610728     1879 388 4503  1009
210 0.050    0.10 0.7236936 0.7119167 0.29811342     1855 386 4527  1011
211 0.050    0.11 0.7258411 0.7129451 0.25275930     1850 383 4532  1014
212 0.050    0.12 0.7272727 0.7146163 0.26110308     1839 381 4543  1016
213 0.050    0.13 0.7287044 0.7162874 0.26965760     1828 379 4554  1018
214 0.050    0.14 0.7308518 0.7180872 0.25517331     1817 376 4565  1021
215 0.050    0.15 0.7351467 0.7213009 0.21447056     1798 370 4584  1027
216 0.050    0.16 0.7380100 0.7232292 0.18343284     1787 366 4595  1031
217 0.050    0.17 0.7394417 0.7254146 0.20628750     1772 364 4610  1033
218 0.050    0.18 0.7401575 0.7261859 0.20773736     1767 363 4615  1034
219 0.050    0.19 0.7408733 0.7273428 0.22223756     1759 362 4623  1035
220 0.050    0.20 0.7423049 0.7279856 0.19543916     1756 360 4626  1037
221 0.050    0.21 0.7437366 0.7288855 0.17850736     1751 358 4631  1039
222 0.050    0.22 0.7437366 0.7295282 0.19821303     1746 358 4636  1039
223 0.050    0.23 0.7458840 0.7306852 0.16742132     1740 355 4642  1042
224 0.050    0.24 0.7487473 0.7319707 0.12611141     1734 351 4648  1046
225 0.050    0.25 0.7487473 0.7336419 0.16861757     1721 351 4661  1046
226 0.050    0.26 0.7487473 0.7353130 0.22128665     1708 351 4674  1046
227 0.050    0.27 0.7501790 0.7373698 0.24298557     1694 349 4688  1048
228 0.050    0.28 0.7516106 0.7383983 0.22747316     1688 347 4694  1050
229 0.050    0.29 0.7530422 0.7394267 0.21264006     1682 345 4700  1052
230 0.050    0.30 0.7551897 0.7403265 0.17220448     1678 342 4704  1055
231 0.050    0.31 0.7559055 0.7414835 0.18498549     1670 341 4712  1056
232 0.050    0.32 0.7587688 0.7432832 0.15298764     1660 337 4722  1060
233 0.050    0.33 0.7587688 0.7436689 0.16352540     1657 337 4725  1060
234 0.050    0.34 0.7594846 0.7444402 0.16469880     1652 336 4730  1061
235 0.050    0.35 0.7602004 0.7454686 0.17330147     1645 335 4737  1062
236 0.050    0.36 0.7609162 0.7463684 0.17836446     1639 334 4743  1063
237 0.050    0.37 0.7623479 0.7473968 0.16577398     1633 332 4749  1065
238 0.050    0.38 0.7637795 0.7480396 0.14372335     1630 330 4752  1067
239 0.050    0.39 0.7644953 0.7486823 0.14149252     1626 329 4756  1068
240 0.050    0.40 0.7644953 0.7490680 0.15148669     1623 329 4759  1068
241 0.050    0.41 0.7652112 0.7497108 0.14916567     1619 328 4763  1069
242 0.050    0.42 0.7687903 0.7512534 0.10103390     1612 323 4770  1074
243 0.050    0.43 0.7695061 0.7521532 0.10431951     1606 322 4776  1075
244 0.050    0.44 0.7702219 0.7526674 0.10003617     1603 321 4779  1076
245 0.050    0.45 0.7702219 0.7531816 0.11035142     1599 321 4783  1076
246 0.050    0.46 0.7702219 0.7533102 0.11305955     1598 321 4784  1076
247 0.050    0.47 0.7716535 0.7539530 0.09660045     1595 319 4787  1078
248 0.050    0.48 0.7723694 0.7553670 0.11009411     1585 318 4797  1079
249 0.050    0.49 0.7723694 0.7563954 0.13330689     1577 318 4805  1079
250 0.050    0.50 0.7730852 0.7571667 0.13427242     1572 317 4810  1080
251 0.050    0.51 0.7752326 0.7579380 0.10275072     1569 314 4813  1083
252 0.050    0.52 0.7752326 0.7585808 0.11614508     1564 314 4818  1083
253 0.050    0.53 0.7752326 0.7598663 0.14710167     1554 314 4828  1083
254 0.050    0.54 0.7759485 0.7606376 0.14815568     1549 313 4833  1084
255 0.050    0.55 0.7773801 0.7616660 0.13694405     1543 311 4839  1086
256 0.050    0.56 0.7788117 0.7623088 0.11755359     1540 309 4842  1088
257 0.050    0.57 0.7795276 0.7633372 0.12426472     1533 308 4849  1089
258 0.050    0.58 0.7802434 0.7643656 0.13128938     1526 307 4856  1090
259 0.050    0.59 0.7816750 0.7652655 0.11809676     1521 305 4861  1092
260 0.050    0.60 0.7823908 0.7657797 0.11327433     1518 304 4864  1093
261 0.050    0.61 0.7838225 0.7666795 0.10149492     1513 302 4869  1095
262 0.050    0.62 0.7838225 0.7678365 0.12665871     1504 302 4878  1095
263 0.050    0.63 0.7838225 0.7686078 0.14602510     1498 302 4884  1095
264 0.050    0.64 0.7845383 0.7695076 0.15052874     1492 301 4890  1096
265 0.050    0.65 0.7852541 0.7707932 0.16618696     1483 300 4899  1097
266 0.050    0.66 0.7866858 0.7715645 0.14675005     1479 298 4903  1099
267 0.050    0.67 0.7881174 0.7720787 0.12295060     1477 296 4905  1101
268 0.050    0.68 0.7888332 0.7728500 0.12383190     1472 295 4910  1102
269 0.050    0.69 0.7895490 0.7740069 0.13409624     1464 294 4918  1103
270 0.050    0.70 0.7902649 0.7745211 0.12869704     1461 293 4921  1104
271 0.050    0.71 0.7909807 0.7749068 0.12046987     1459 292 4923  1105
272 0.050    0.72 0.7909807 0.7752925 0.12961488     1456 292 4926  1105
273 0.050    0.73 0.7916965 0.7765780 0.14366440     1447 291 4935  1106
274 0.050    0.74 0.7916965 0.7770922 0.15780299     1443 291 4939  1106
275 0.050    0.75 0.7916965 0.7783777 0.19785022     1433 291 4949  1106
276 0.050    0.76 0.7931281 0.7799203 0.20058954     1423 289 4959  1108
277 0.050    0.77 0.7931281 0.7806916 0.22836993     1417 289 4965  1108
278 0.050    0.78 0.7945598 0.7817200 0.21243806     1411 287 4971  1110
279 0.050    0.79 0.7952756 0.7827484 0.22332433     1404 286 4978  1111
280 0.050    0.80 0.7974230 0.7841625 0.19560381     1396 283 4986  1114
281 0.050    0.81 0.7981389 0.7857051 0.22459273     1385 282 4997  1115
282 0.050    0.82 0.7981389 0.7866050 0.26032018     1378 282 5004  1115
283 0.050    0.83 0.8010021 0.7878905 0.19796159     1372 278 5010  1119
284 0.050    0.84 0.8010021 0.7885332 0.22100596     1367 278 5015  1119
285 0.050    0.85 0.8010021 0.7891760 0.24596842     1362 278 5020  1119
286 0.050    0.86 0.8031496 0.7907186 0.22069433     1353 275 5029  1122
287 0.050    0.87 0.8052971 0.7926469 0.21086948     1341 272 5041  1125
288 0.050    0.88 0.8095920 0.7943180 0.12781141     1334 266 5048  1131
289 0.050    0.89 0.8131711 0.7959892 0.08492819     1326 261 5056  1136
290 0.050    0.90 0.8146027 0.7963749 0.06707391     1325 259 5057  1138
291 0.050    0.91 0.8160344 0.7975318 0.06242327     1318 257 5064  1140
292 0.050    0.92 0.8188976 0.8001028 0.05712390     1302 253 5080  1144
293 0.050    0.93 0.8188976 0.8025453 0.09731979     1283 253 5099  1144
294 0.050    0.94 0.8224767 0.8051163 0.07652100     1268 248 5114  1149
295 0.050    0.95 0.8239084 0.8082016 0.10768080     1246 246 5136  1151
296 0.050    0.96 0.8282033 0.8119296 0.09282022     1223 240 5159  1157
297 0.050    0.97 0.8339298 0.8175858 0.08760626     1187 232 5195  1165
298 0.050    0.98 0.8389406 0.8227279 0.08668548     1154 225 5228  1172
299 0.050    0.99 0.8468146 0.8295411 0.06341529     1112 214 5270  1183
300 0.050    1.00 1.0000000 1.0000000 0.00000000        0   0 6382  1397
301 0.075    0.01 0.6847458 0.6751510 0.34118268     1969 558 4040  1212
302 0.075    0.02 0.6966102 0.6855637 0.26710109     1909 537 4100  1233
303 0.075    0.03 0.7005650 0.6898059 0.27830039     1883 530 4126  1240
304 0.075    0.04 0.7067797 0.6949479 0.22986423     1854 519 4155  1251
305 0.075    0.05 0.7101695 0.6986759 0.24215891     1831 513 4178  1257
306 0.075    0.06 0.7124294 0.7018897 0.28310134     1810 509 4199  1261
307 0.075    0.07 0.7152542 0.7040751 0.25315330     1798 504 4211  1266
308 0.075    0.08 0.7169492 0.7063890 0.28002011     1783 501 4226  1269
309 0.075    0.09 0.7180791 0.7085744 0.33131651     1768 499 4241  1271
310 0.075    0.10 0.7197740 0.7119167 0.42333027     1745 496 4264  1274
311 0.075    0.11 0.7214689 0.7129451 0.38318886     1740 493 4269  1277
312 0.075    0.12 0.7225989 0.7146163 0.41438932     1729 491 4280  1279
313 0.075    0.13 0.7237288 0.7162874 0.44715375     1718 489 4291  1281
314 0.075    0.14 0.7254237 0.7180872 0.45296256     1707 486 4302  1284
315 0.075    0.15 0.7288136 0.7213009 0.44016652     1688 480 4321  1290
316 0.075    0.16 0.7322034 0.7232292 0.35240330     1679 474 4330  1296
317 0.075    0.17 0.7333333 0.7254146 0.41277254     1664 472 4345  1298
318 0.075    0.18 0.7344633 0.7261859 0.39075973     1660 470 4349  1300
319 0.075    0.19 0.7350282 0.7273428 0.42618205     1652 469 4357  1301
320 0.075    0.20 0.7361582 0.7279856 0.39602802     1649 467 4360  1303
321 0.075    0.21 0.7372881 0.7288855 0.38190336     1644 465 4365  1305
322 0.075    0.22 0.7384181 0.7295282 0.35364233     1641 463 4368  1307
323 0.075    0.23 0.7412429 0.7306852 0.26752492     1637 458 4372  1312
324 0.075    0.24 0.7435028 0.7319707 0.22407579     1631 454 4378  1316
325 0.075    0.25 0.7435028 0.7336419 0.29963533     1618 454 4391  1316
326 0.075    0.26 0.7440678 0.7353130 0.35795143     1606 453 4403  1317
327 0.075    0.27 0.7457627 0.7373698 0.37766119     1593 450 4416  1320
328 0.075    0.28 0.7468927 0.7383983 0.37111390     1587 448 4422  1322
329 0.075    0.29 0.7480226 0.7394267 0.36461778     1581 446 4428  1324
330 0.075    0.30 0.7502825 0.7403265 0.29092291     1578 442 4431  1328
331 0.075    0.31 0.7508475 0.7414835 0.32075406     1570 441 4439  1329
332 0.075    0.32 0.7542373 0.7432832 0.24223197     1562 435 4447  1335
333 0.075    0.33 0.7548023 0.7436689 0.23417929     1560 434 4449  1336
334 0.075    0.34 0.7559322 0.7444402 0.21862330     1556 432 4453  1338
335 0.075    0.35 0.7564972 0.7454686 0.23764180     1549 431 4460  1339
336 0.075    0.36 0.7570621 0.7463684 0.25202807     1543 430 4466  1340
337 0.075    0.37 0.7581921 0.7473968 0.24679780     1537 428 4472  1342
338 0.075    0.38 0.7593220 0.7480396 0.22518423     1534 426 4475  1344
339 0.075    0.39 0.7598870 0.7486823 0.22808655     1530 425 4479  1345
340 0.075    0.40 0.7604520 0.7490680 0.22030545     1528 424 4481  1346
341 0.075    0.41 0.7610169 0.7497108 0.22316036     1524 423 4485  1347
342 0.075    0.42 0.7644068 0.7512534 0.15409053     1518 417 4491  1353
343 0.075    0.43 0.7649718 0.7521532 0.16457948     1512 416 4497  1354
344 0.075    0.44 0.7655367 0.7526674 0.16258375     1509 415 4500  1355
345 0.075    0.45 0.7661017 0.7531816 0.16060278     1506 414 4503  1356
346 0.075    0.46 0.7666667 0.7533102 0.14657011     1506 413 4503  1357
347 0.075    0.47 0.7677966 0.7539530 0.13176597     1503 411 4506  1359
348 0.075    0.48 0.7689266 0.7553670 0.13928192     1494 409 4515  1361
349 0.075    0.49 0.7689266 0.7563954 0.17197098     1486 409 4523  1361
350 0.075    0.50 0.7694915 0.7571667 0.17884027     1481 408 4528  1362
351 0.075    0.51 0.7711864 0.7579380 0.14733560     1478 405 4531  1365
352 0.075    0.52 0.7711864 0.7585808 0.16807255     1473 405 4536  1365
353 0.075    0.53 0.7711864 0.7598663 0.21613032     1463 405 4546  1365
354 0.075    0.54 0.7717514 0.7606376 0.22432835     1458 404 4551  1366
355 0.075    0.55 0.7728814 0.7616660 0.21933338     1452 402 4557  1368
356 0.075    0.56 0.7740113 0.7623088 0.19906154     1449 400 4560  1370
357 0.075    0.57 0.7745763 0.7633372 0.21721914     1442 399 4567  1371
358 0.075    0.58 0.7751412 0.7643656 0.23659439     1435 398 4574  1372
359 0.075    0.59 0.7768362 0.7652655 0.20234259     1431 395 4578  1375
360 0.075    0.60 0.7774011 0.7657797 0.19997811     1428 394 4581  1376
361 0.075    0.61 0.7785311 0.7666795 0.19040909     1423 392 4586  1378
362 0.075    0.62 0.7785311 0.7678365 0.23781373     1414 392 4595  1378
363 0.075    0.63 0.7785311 0.7686078 0.27382650     1408 392 4601  1378
364 0.075    0.64 0.7796610 0.7695076 0.26188902     1403 390 4606  1380
365 0.075    0.65 0.7802260 0.7707932 0.29737352     1394 389 4615  1381
366 0.075    0.66 0.7813559 0.7715645 0.27827180     1390 387 4619  1383
367 0.075    0.67 0.7824859 0.7720787 0.24795425     1388 385 4621  1385
368 0.075    0.68 0.7836158 0.7728500 0.23103859     1384 383 4625  1387
369 0.075    0.69 0.7841808 0.7740069 0.25759371     1376 382 4633  1388
370 0.075    0.70 0.7847458 0.7745211 0.25477580     1373 381 4636  1389
371 0.075    0.71 0.7853107 0.7749068 0.24602036     1371 380 4638  1390
372 0.075    0.72 0.7853107 0.7752925 0.26418784     1368 380 4641  1390
373 0.075    0.73 0.7864407 0.7765780 0.27091838     1360 378 4649  1392
374 0.075    0.74 0.7864407 0.7770922 0.29708077     1356 378 4653  1392
375 0.075    0.75 0.7864407 0.7783777 0.36987208     1346 378 4663  1392
376 0.075    0.76 0.7875706 0.7799203 0.39461393     1336 376 4673  1394
377 0.075    0.77 0.7875706 0.7806916 0.44538896     1330 376 4679  1394
378 0.075    0.78 0.7892655 0.7817200 0.39998229     1325 373 4684  1397
379 0.075    0.79 0.7903955 0.7827484 0.39262082     1319 371 4690  1399
380 0.075    0.80 0.7920904 0.7841625 0.37369441     1311 368 4698  1402
381 0.075    0.81 0.7926554 0.7857051 0.43666063     1300 367 4709  1403
382 0.075    0.82 0.7926554 0.7866050 0.50037427     1293 367 4716  1403
383 0.075    0.83 0.7949153 0.7878905 0.42983050     1287 363 4722  1407
384 0.075    0.84 0.7954802 0.7885332 0.43466127     1283 362 4726  1408
385 0.075    0.85 0.7954802 0.7891760 0.47976473     1278 362 4731  1408
386 0.075    0.86 0.7971751 0.7907186 0.46752623     1269 359 4740  1411
387 0.075    0.87 0.8000000 0.7926469 0.40379915     1259 354 4750  1416
388 0.075    0.88 0.8033898 0.7943180 0.29792439     1252 348 4757  1422
389 0.075    0.89 0.8067797 0.7959892 0.21195568     1245 342 4764  1428
390 0.075    0.90 0.8079096 0.7963749 0.18104036     1244 340 4765  1430
391 0.075    0.91 0.8090395 0.7975318 0.18116288     1237 338 4772  1432
392 0.075    0.92 0.8118644 0.8001028 0.16944999     1222 333 4787  1437
393 0.075    0.93 0.8118644 0.8025453 0.27719749     1203 333 4806  1437
394 0.075    0.94 0.8146893 0.8051163 0.26156166     1188 328 4821  1442
395 0.075    0.95 0.8158192 0.8082016 0.37249258     1166 326 4843  1444
396 0.075    0.96 0.8203390 0.8119296 0.31947763     1145 318 4864  1452
397 0.075    0.97 0.8276836 0.8175858 0.22374773     1114 305 4895  1465
398 0.075    0.98 0.8333333 0.8227279 0.19569597     1084 295 4925  1475
399 0.075    0.99 0.8406780 0.8295411 0.16705310     1044 282 4965  1488
400 0.075    1.00 1.0000000 1.0000000 0.00000000        0   0 6009  1770
401 0.100    0.01 0.6883365 0.6751510 0.13919221     1875 652 3812  1440
402 0.100    0.02 0.6998088 0.6855637 0.10658844     1818 628 3869  1464
403 0.100    0.03 0.7036329 0.6898059 0.11609860     1793 620 3894  1472
404 0.100    0.04 0.7108031 0.6949479 0.06963030     1768 605 3919  1487
405 0.100    0.05 0.7146272 0.6986759 0.06697752     1747 597 3940  1495
406 0.100    0.06 0.7170172 0.7018897 0.08166225     1727 592 3960  1500
407 0.100    0.07 0.7194073 0.7040751 0.07692518     1715 587 3972  1505
408 0.100    0.08 0.7213193 0.7063890 0.08440983     1701 583 3986  1509
409 0.100    0.09 0.7227533 0.7085744 0.10079907     1687 580 4000  1512
410 0.100    0.10 0.7246654 0.7119167 0.13949933     1665 576 4022  1516
411 0.100    0.11 0.7260994 0.7129451 0.12671166     1660 573 4027  1519
412 0.100    0.12 0.7270554 0.7146163 0.14841297     1649 571 4038  1521
413 0.100    0.13 0.7280115 0.7162874 0.17292773     1638 569 4049  1523
414 0.100    0.14 0.7299235 0.7180872 0.16794393     1628 565 4059  1527
415 0.100    0.15 0.7332696 0.7213009 0.16167525     1610 558 4077  1534
416 0.100    0.16 0.7361377 0.7232292 0.12981808     1601 552 4086  1540
417 0.100    0.17 0.7370937 0.7254146 0.17031409     1586 550 4101  1542
418 0.100    0.18 0.7380497 0.7261859 0.16315010     1582 548 4105  1544
419 0.100    0.19 0.7390057 0.7273428 0.16998205     1575 546 4112  1546
420 0.100    0.20 0.7399618 0.7279856 0.15826430     1572 544 4115  1548
421 0.100    0.21 0.7409178 0.7288855 0.15585274     1567 542 4120  1550
422 0.100    0.22 0.7418738 0.7295282 0.14485617     1564 540 4123  1552
423 0.100    0.23 0.7442639 0.7306852 0.10770129     1560 535 4127  1557
424 0.100    0.24 0.7461759 0.7319707 0.09165813     1554 531 4133  1561
425 0.100    0.25 0.7461759 0.7336419 0.13679309     1541 531 4146  1561
426 0.100    0.26 0.7466539 0.7353130 0.17825192     1529 530 4158  1562
427 0.100    0.27 0.7490440 0.7373698 0.16451681     1518 525 4169  1567
428 0.100    0.28 0.7500000 0.7383983 0.16666833     1512 523 4175  1569
429 0.100    0.29 0.7509560 0.7394267 0.16884345     1506 521 4181  1571
430 0.100    0.30 0.7528681 0.7403265 0.13336463     1503 517 4184  1575
431 0.100    0.31 0.7533461 0.7414835 0.15555220     1495 516 4192  1576
432 0.100    0.32 0.7562141 0.7432832 0.12012128     1487 510 4200  1582
433 0.100    0.33 0.7566922 0.7436689 0.11726766     1485 509 4202  1583
434 0.100    0.34 0.7576482 0.7444402 0.11171114     1481 507 4206  1585
435 0.100    0.35 0.7581262 0.7454686 0.12724226     1474 506 4213  1586
436 0.100    0.36 0.7586042 0.7463684 0.14021689     1468 505 4219  1587
437 0.100    0.37 0.7595602 0.7473968 0.14208947     1462 503 4225  1589
438 0.100    0.38 0.7609943 0.7480396 0.11716300     1460 500 4227  1592
439 0.100    0.39 0.7614723 0.7486823 0.12166915     1456 499 4231  1593
440 0.100    0.40 0.7619503 0.7490680 0.11876197     1454 498 4233  1594
441 0.100    0.41 0.7624283 0.7497108 0.12332194     1450 497 4237  1595
442 0.100    0.42 0.7657744 0.7512534 0.07717255     1445 490 4242  1602
443 0.100    0.43 0.7667304 0.7521532 0.07566091     1440 488 4247  1604
444 0.100    0.44 0.7672084 0.7526674 0.07619759     1437 487 4250  1605
445 0.100    0.45 0.7681644 0.7531816 0.06736310     1435 485 4252  1607
446 0.100    0.46 0.7686424 0.7533102 0.06107821     1435 484 4252  1608
447 0.100    0.47 0.7695985 0.7539530 0.05568642     1432 482 4255  1610
448 0.100    0.48 0.7710325 0.7553670 0.05489680     1424 479 4263  1613
449 0.100    0.49 0.7715105 0.7563954 0.06376181     1417 478 4270  1614
450 0.100    0.50 0.7724665 0.7571667 0.06026069     1413 476 4274  1616
451 0.100    0.51 0.7739006 0.7579380 0.04956705     1410 473 4277  1619
452 0.100    0.52 0.7739006 0.7585808 0.05941429     1405 473 4282  1619
453 0.100    0.53 0.7743786 0.7598663 0.07386769     1396 472 4291  1620
454 0.100    0.54 0.7748566 0.7606376 0.07966521     1391 471 4296  1621
455 0.100    0.55 0.7758126 0.7616660 0.08078757     1385 469 4302  1623
456 0.100    0.56 0.7767686 0.7623088 0.07391735     1382 467 4305  1625
457 0.100    0.57 0.7777247 0.7633372 0.07496375     1376 465 4311  1627
458 0.100    0.58 0.7786807 0.7643656 0.07602302     1370 463 4317  1629
459 0.100    0.59 0.7801147 0.7652655 0.06518095     1366 460 4321  1632
460 0.100    0.60 0.7805927 0.7657797 0.06564404     1363 459 4324  1633
461 0.100    0.61 0.7820268 0.7666795 0.05602100     1359 456 4328  1636
462 0.100    0.62 0.7825048 0.7678365 0.06752519     1351 455 4336  1637
463 0.100    0.63 0.7825048 0.7686078 0.08319329     1345 455 4342  1637
464 0.100    0.64 0.7834608 0.7695076 0.08151751     1340 453 4347  1639
465 0.100    0.65 0.7839388 0.7707932 0.10046569     1331 452 4356  1640
466 0.100    0.66 0.7848948 0.7715645 0.09529895     1327 450 4360  1642
467 0.100    0.67 0.7858509 0.7720787 0.08439249     1325 448 4362  1644
468 0.100    0.68 0.7868069 0.7728500 0.07987751     1321 446 4366  1646
469 0.100    0.69 0.7872849 0.7740069 0.09537092     1313 445 4374  1647
470 0.100    0.70 0.7877629 0.7745211 0.09602548     1310 444 4377  1648
471 0.100    0.71 0.7882409 0.7749068 0.09348863     1308 443 4379  1649
472 0.100    0.72 0.7882409 0.7752925 0.10334045     1305 443 4382  1649
473 0.100    0.73 0.7891969 0.7765780 0.11186121     1297 441 4390  1651
474 0.100    0.74 0.7891969 0.7770922 0.12723454     1293 441 4394  1651
475 0.100    0.75 0.7891969 0.7783777 0.17298211     1283 441 4404  1651
476 0.100    0.76 0.7901530 0.7799203 0.19692603     1273 439 4414  1653
477 0.100    0.77 0.7901530 0.7806916 0.23315451     1267 439 4420  1653
478 0.100    0.78 0.7915870 0.7817200 0.21246370     1262 436 4425  1656
479 0.100    0.79 0.7925430 0.7827484 0.21513977     1256 434 4431  1658
480 0.100    0.80 0.7939771 0.7841625 0.21310067     1248 431 4439  1661
481 0.100    0.81 0.7954111 0.7857051 0.21713754     1239 428 4448  1664
482 0.100    0.82 0.7958891 0.7866050 0.23760737     1233 427 4454  1665
483 0.100    0.83 0.7982792 0.7878905 0.18413536     1228 422 4459  1670
484 0.100    0.84 0.7992352 0.7885332 0.17048661     1225 420 4462  1672
485 0.100    0.85 0.7997132 0.7891760 0.17683481     1221 419 4466  1673
486 0.100    0.86 0.8016252 0.7907186 0.16067930     1213 415 4474  1677
487 0.100    0.87 0.8040153 0.7926469 0.14196428     1203 410 4484  1682
488 0.100    0.88 0.8068834 0.7943180 0.10282265     1196 404 4491  1688
489 0.100    0.89 0.8097514 0.7959892 0.07262946     1189 398 4498  1694
490 0.100    0.90 0.8107075 0.7963749 0.06118120     1188 396 4499  1696
491 0.100    0.91 0.8116635 0.7975318 0.06439811     1181 394 4506  1698
492 0.100    0.92 0.8140535 0.8001028 0.06664361     1166 389 4521  1703
493 0.100    0.93 0.8140535 0.8025453 0.12993701     1147 389 4540  1703
494 0.100    0.94 0.8164436 0.8051163 0.13428091     1132 384 4555  1708
495 0.100    0.95 0.8173996 0.8082016 0.22350847     1110 382 4577  1710
496 0.100    0.96 0.8217017 0.8119296 0.19188458     1090 373 4597  1719
497 0.100    0.97 0.8283939 0.8175858 0.14319327     1060 359 4627  1733
498 0.100    0.98 0.8331740 0.8227279 0.15279214     1030 349 4657  1743
499 0.100    0.99 0.8408222 0.8295411 0.11622647      993 333 4694  1759
500 0.100    1.00 1.0000000 1.0000000 0.00000000        0   0 5687  2092
#FIGS20C/D
enrichment.plotter(gene.hic.filt, "weighted_Z.ALLvar.H", "adj.P.Val", "FDR for Weighted p-val Combine of Hi-C Contacts Overlapping Gene", xmax=1) #FIGS20C/D
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
    DEFDR DHICFDR   prop.obs  prop.exp     chisq.p Dneither   DE DHiC
1   0.010    0.01 0.11276596 0.0951829 0.208016631     6608  417  686
2   0.010    0.02 0.14042553 0.1209428 0.206411215     6421  404  873
3   0.010    0.03 0.17659574 0.1448995 0.051598443     6252  387 1042
4   0.010    0.04 0.19574468 0.1664091 0.089537761     6094  378 1200
5   0.010    0.05 0.21914894 0.1846986 0.054308116     5963  367 1331
6   0.010    0.06 0.24255319 0.2005410 0.022171252     5851  356 1443
7   0.010    0.07 0.25531915 0.2153529 0.034279757     5742  350 1552
8   0.010    0.08 0.28085106 0.2315817 0.010589334     5628  338 1666
9   0.010    0.09 0.29787234 0.2461360 0.008509428     5523  330 1771
10  0.010    0.10 0.31914894 0.2592736 0.002685010     5431  320 1863
11  0.010    0.11 0.33404255 0.2753735 0.003921862     5313  313 1981
12  0.010    0.12 0.34893617 0.2881247 0.003169677     5221  306 2073
13  0.010    0.13 0.35744681 0.2982998 0.004517071     5146  302 2148
14  0.010    0.14 0.37021277 0.3082174 0.003162717     5075  296 2219
15  0.010    0.15 0.37659574 0.3212262 0.009287748     4977  293 2317
16  0.010    0.16 0.39148936 0.3323029 0.005781496     4898  286 2396
17  0.010    0.17 0.40851064 0.3444101 0.003005156     4812  278 2482
18  0.010    0.18 0.41489362 0.3563885 0.007304740     4722  275 2572
19  0.010    0.19 0.42553191 0.3633436 0.004475023     4673  270 2621
20  0.010    0.20 0.43829787 0.3733900 0.003154950     4601  264 2693
21  0.010    0.21 0.45319149 0.3858836 0.002336846     4511  257 2783
22  0.010    0.22 0.45319149 0.3956723 0.009813923     4435  257 2859
23  0.010    0.23 0.46170213 0.4045595 0.010599737     4370  253 2924
24  0.010    0.24 0.46808511 0.4149923 0.018183675     4292  250 3002
25  0.010    0.25 0.48085106 0.4234930 0.010825587     4232  244 3062
26  0.010    0.26 0.48297872 0.4328954 0.026907126     4160  243 3134
27  0.010    0.27 0.49148936 0.4434570 0.034458809     4082  239 3212
28  0.010    0.28 0.50425532 0.4545337 0.028836375     4002  233 3292
29  0.010    0.29 0.50851064 0.4645801 0.054551271     3926  231 3368
30  0.010    0.30 0.51702128 0.4733385 0.056231450     3862  227 3432
31  0.010    0.31 0.52127660 0.4841577 0.106591703     3780  225 3514
32  0.010    0.32 0.52553191 0.4945904 0.181343725     3701  223 3593
33  0.010    0.33 0.54680851 0.5038640 0.060992266     3639  213 3655
34  0.010    0.34 0.55531915 0.5117208 0.057005510     3582  209 3712
35  0.010    0.35 0.56170213 0.5204791 0.072178080     3517  206 3777
36  0.010    0.36 0.56808511 0.5278207 0.079033219     3463  203 3831
37  0.010    0.37 0.57446809 0.5350335 0.085303249     3410  200 3884
38  0.010    0.38 0.58085106 0.5421175 0.090811207     3358  197 3936
39  0.010    0.39 0.59574468 0.5508758 0.048861073     3297  190 3997
40  0.010    0.40 0.60000000 0.5580886 0.065806877     3243  188 4051
41  0.010    0.41 0.60638298 0.5659454 0.075589229     3185  185 4109
42  0.010    0.42 0.61063830 0.5739310 0.106918037     3125  183 4169
43  0.010    0.43 0.61914894 0.5829469 0.110944677     3059  179 4235
44  0.010    0.44 0.63191489 0.5914477 0.072986300     2999  173 4295
45  0.010    0.45 0.64468085 0.5999485 0.046183471     2939  167 4355
46  0.010    0.46 0.65531915 0.6079341 0.033822951     2882  162 4412
47  0.010    0.47 0.65957447 0.6159196 0.050155466     2822  160 4472
48  0.010    0.48 0.66595745 0.6239052 0.058409274     2763  157 4531
49  0.010    0.49 0.68085106 0.6322772 0.027535505     2705  150 4589
50  0.010    0.50 0.68723404 0.6385884 0.026737353     2659  147 4635
51  0.010    0.51 0.69361702 0.6455435 0.027940455     2608  144 4686
52  0.010    0.52 0.70851064 0.6534003 0.011078035     2554  137 4740
53  0.010    0.53 0.71702128 0.6625451 0.011517537     2487  133 4807
54  0.010    0.54 0.72127660 0.6700155 0.016949030     2431  131 4863
55  0.010    0.55 0.73617021 0.6789026 0.007092339     2369  124 4925
56  0.010    0.56 0.74042553 0.6863730 0.010634161     2313  122 4981
57  0.010    0.57 0.75106383 0.6946162 0.007152631     2254  117 5040
58  0.010    0.58 0.75957447 0.7022154 0.005895098     2199  113 5095
59  0.010    0.59 0.76595745 0.7108449 0.007664621     2135  110 5159
60  0.010    0.60 0.77021277 0.7174137 0.010169555     2086  108 5208
61  0.010    0.61 0.78723404 0.7246265 0.002059002     2038  100 5256
62  0.010    0.62 0.79148936 0.7317105 0.003036096     1985   98 5309
63  0.010    0.63 0.79787234 0.7396960 0.003600378     1926   95 5368
64  0.010    0.64 0.80425532 0.7465224 0.003570278     1876   92 5418
65  0.010    0.65 0.81489362 0.7545080 0.002049300     1819   87 5475
66  0.010    0.66 0.81914894 0.7613344 0.002903112     1768   85 5526
67  0.010    0.67 0.82978723 0.7690623 0.001543156     1713   80 5581
68  0.010    0.68 0.83617021 0.7774343 0.001928142     1651   77 5643
69  0.010    0.69 0.84468085 0.7856775 0.001587936     1591   73 5703
70  0.010    0.70 0.84893617 0.7921175 0.002117914     1543   71 5751
71  0.010    0.71 0.84893617 0.7980422 0.005499127     1497   71 5797
72  0.010    0.72 0.85531915 0.8070582 0.007468151     1430   68 5864
73  0.010    0.73 0.85957447 0.8143998 0.011157269     1375   66 5919
74  0.010    0.74 0.86170213 0.8207110 0.019905254     1327   65 5967
75  0.010    0.75 0.86808511 0.8274086 0.019046089     1278   62 6016
76  0.010    0.76 0.86808511 0.8339773 0.047002537     1227   62 6067
77  0.010    0.77 0.87446809 0.8414477 0.050359115     1172   59 6122
78  0.010    0.78 0.87659574 0.8482741 0.089239063     1120   58 6174
79  0.010    0.79 0.88085106 0.8571613 0.148089816     1053   56 6241
80  0.010    0.80 0.88510638 0.8642452 0.196092797     1000   54 6294
81  0.010    0.81 0.88936170 0.8691396 0.203863682      964   52 6330
82  0.010    0.82 0.89148936 0.8760948 0.330615516      911   51 6383
83  0.010    0.83 0.89574468 0.8824060 0.394040475      864   49 6430
84  0.010    0.84 0.90212766 0.8898764 0.424088692      809   46 6485
85  0.010    0.85 0.90851064 0.8973467 0.456675234      754   43 6540
86  0.010    0.86 0.91276596 0.9048171 0.599755390      698   41 6596
87  0.010    0.87 0.91914894 0.9128027 0.675365372      639   38 6655
88  0.010    0.88 0.92978723 0.9188563 0.418943154      597   33 6697
89  0.010    0.89 0.93404255 0.9264554 0.576182799      540   31 6754
90  0.010    0.90 0.94255319 0.9339258 0.495856320      486   27 6808
91  0.010    0.91 0.94893617 0.9406234 0.492669041      437   24 6857
92  0.010    0.92 0.95106383 0.9479650 0.837615472      381   23 6913
93  0.010    0.93 0.95744681 0.9544049 0.832038000      334   20 6960
94  0.010    0.94 0.96595745 0.9612313 0.671322516      285   16 7009
95  0.010    0.95 0.97021277 0.9687017 0.954186719      229   14 7065
96  0.010    0.96 0.97659574 0.9741113 0.841408218      190   11 7104
97  0.010    0.97 0.98297872 0.9802937 0.794170336      145    8 7149
98  0.010    0.98 0.99148936 0.9875064 0.556653886       93    4 7201
99  0.010    0.99 0.99361702 0.9920144 0.892300997       59    3 7235
100 0.010    1.00 1.00000000 1.0000000 0.000000000        0    0 7294
101 0.025    0.01 0.10725894 0.0951829 0.203342669     6201  824  640
102 0.025    0.02 0.13542795 0.1209428 0.166340232     6027  798  814
103 0.025    0.03 0.16359697 0.1448995 0.095042111     5867  772  974
104 0.025    0.04 0.18309859 0.1664091 0.160544735     5718  754 1123
105 0.025    0.05 0.20910076 0.1846986 0.046581728     5600  730 1241
106 0.025    0.06 0.22968581 0.2005410 0.020774749     5496  711 1345
107 0.025    0.07 0.23943662 0.2153529 0.063797299     5390  702 1451
108 0.025    0.08 0.26327194 0.2315817 0.016855172     5286  680 1555
109 0.025    0.09 0.28169014 0.2461360 0.008520845     5190  663 1651
110 0.025    0.10 0.30335861 0.2592736 0.001300533     5108  643 1733
111 0.025    0.11 0.31202600 0.2753735 0.008886512     4991  635 1850
112 0.025    0.12 0.32177681 0.2881247 0.017970430     4901  626 1940
113 0.025    0.13 0.32719393 0.2982998 0.044885802     4827  621 2014
114 0.025    0.14 0.33802817 0.3082174 0.040214866     4760  611 2081
115 0.025    0.15 0.34452871 0.3212262 0.114651729     4665  605 2176
116 0.025    0.16 0.35861322 0.3323029 0.076629384     4592  592 2249
117 0.025    0.17 0.37161430 0.3444101 0.069360983     4510  580 2331
118 0.025    0.18 0.38136511 0.3563885 0.098680879     4426  571 2415
119 0.025    0.19 0.39219935 0.3633436 0.056735175     4382  561 2459
120 0.025    0.20 0.40195016 0.3733900 0.060824457     4313  552 2528
121 0.025    0.21 0.41386782 0.3858836 0.068069638     4227  541 2614
122 0.025    0.22 0.42145179 0.3956723 0.094832833     4158  534 2683
123 0.025    0.23 0.42795233 0.4045595 0.131839548     4095  528 2746
124 0.025    0.24 0.43445287 0.4149923 0.213965427     4020  522 2821
125 0.025    0.25 0.44962080 0.4234930 0.093747605     3968  508 2873
126 0.025    0.26 0.45937161 0.4328954 0.090246743     3904  499 2937
127 0.025    0.27 0.46587216 0.4434570 0.154146400     3828  493 3013
128 0.025    0.28 0.47562297 0.4545337 0.181680426     3751  484 3090
129 0.025    0.29 0.48320693 0.4645801 0.240547391     3680  477 3161
130 0.025    0.30 0.49187432 0.4733385 0.243436089     3620  469 3221
131 0.025    0.31 0.50162514 0.4841577 0.273001602     3545  460 3296
132 0.025    0.32 0.50812568 0.4945904 0.400270915     3470  454 3371
133 0.025    0.33 0.52221018 0.5038640 0.249099040     3411  441 3430
134 0.025    0.34 0.52979415 0.5117208 0.256308825     3357  434 3484
135 0.025    0.35 0.53846154 0.5204791 0.258516050     3297  426 3544
136 0.025    0.36 0.54604550 0.5278207 0.251619970     3247  419 3594
137 0.025    0.37 0.55037920 0.5350335 0.336732245     3195  415 3646
138 0.025    0.38 0.55579632 0.5421175 0.393428537     3145  410 3696
139 0.025    0.39 0.56879740 0.5508758 0.258102022     3089  398 3752
140 0.025    0.40 0.57529794 0.5580886 0.277359189     3039  392 3802
141 0.025    0.41 0.58179848 0.5659454 0.317378735     2984  386 3857
142 0.025    0.42 0.58938245 0.5739310 0.329136600     2929  379 3912
143 0.025    0.43 0.59804984 0.5829469 0.339169369     2867  371 3974
144 0.025    0.44 0.60780065 0.5914477 0.297856895     2810  362 4031
145 0.025    0.45 0.61971831 0.5999485 0.203978459     2755  351 4086
146 0.025    0.46 0.63055255 0.6079341 0.143313091     2703  341 4138
147 0.025    0.47 0.63705309 0.6159196 0.170604818     2647  335 4194
148 0.025    0.48 0.64247021 0.6239052 0.228500165     2590  330 4251
149 0.025    0.49 0.65547129 0.6322772 0.128387482     2537  318 4304
150 0.025    0.50 0.66197183 0.6385884 0.123836095     2494  312 4347
151 0.025    0.51 0.66847237 0.6455435 0.129838383     2446  306 4395
152 0.025    0.52 0.68147346 0.6534003 0.061145156     2397  294 4444
153 0.025    0.53 0.68797400 0.6625451 0.088472904     2332  288 4509
154 0.025    0.54 0.69555796 0.6700155 0.085274150     2281  281 4560
155 0.025    0.55 0.70855905 0.6789026 0.043565635     2224  269 4617
156 0.025    0.56 0.71289274 0.6863730 0.069957221     2170  265 4671
157 0.025    0.57 0.72264355 0.6946162 0.053421311     2115  256 4726
158 0.025    0.58 0.72914410 0.7022154 0.061815349     2062  250 4779
159 0.025    0.59 0.73781148 0.7108449 0.059235416     2003  242 4838
160 0.025    0.60 0.74539545 0.7174137 0.048557186     1959  235 4882
161 0.025    0.61 0.75731311 0.7246265 0.019856667     1914  224 4927
162 0.025    0.62 0.76598050 0.7317105 0.013746915     1867  216 4974
163 0.025    0.63 0.77031419 0.7396960 0.026526364     1809  212 5032
164 0.025    0.64 0.77573131 0.7465224 0.032930025     1761  207 5080
165 0.025    0.65 0.78548212 0.7545080 0.022102636     1708  198 5133
166 0.025    0.66 0.79414951 0.7613344 0.014267660     1663  190 5178
167 0.025    0.67 0.80281690 0.7690623 0.010750241     1611  182 5230
168 0.025    0.68 0.81581798 0.7774343 0.003235837     1558  170 5283
169 0.025    0.69 0.82448537 0.7856775 0.002543112     1502  162 5339
170 0.025    0.70 0.82990249 0.7921175 0.002973234     1457  157 5384
171 0.025    0.71 0.83206934 0.7980422 0.006942751     1413  155 5428
172 0.025    0.72 0.83640303 0.8070582 0.018155945     1347  151 5494
173 0.025    0.73 0.84615385 0.8143998 0.009366570     1299  142 5542
174 0.025    0.74 0.85048754 0.8207110 0.013637222     1254  138 5587
175 0.025    0.75 0.85807151 0.8274086 0.009885582     1209  131 5632
176 0.025    0.76 0.86132178 0.8339773 0.019736435     1161  128 5680
177 0.025    0.77 0.86457205 0.8414477 0.045386734     1106  125 5735
178 0.025    0.78 0.86998917 0.8482741 0.056109193     1058  120 5783
179 0.025    0.79 0.87215601 0.8571613 0.181265384      991  118 5850
180 0.025    0.80 0.87865655 0.8642452 0.190011487      942  112 5899
181 0.025    0.81 0.88407367 0.8691396 0.167207833      909  107 5932
182 0.025    0.82 0.88624052 0.8760948 0.345453790      857  105 5984
183 0.025    0.83 0.89165764 0.8824060 0.381503105      813  100 6028
184 0.025    0.84 0.89815818 0.8898764 0.423565477      761   94 6080
185 0.025    0.85 0.90790899 0.8973467 0.285256869      712   85 6129
186 0.025    0.86 0.91982665 0.9048171 0.110575250      665   74 6176
187 0.025    0.87 0.93066089 0.9128027 0.046970080      613   64 6228
188 0.025    0.88 0.93824485 0.9188563 0.025486841      573   57 6268
189 0.025    0.89 0.94257855 0.9264554 0.053361897      518   53 6323
190 0.025    0.90 0.94907909 0.9339258 0.056943563      466   47 6375
191 0.025    0.91 0.95666306 0.9406234 0.033797870      421   40 6420
192 0.025    0.92 0.95774648 0.9479650 0.178145323      365   39 6476
193 0.025    0.93 0.96099675 0.9544049 0.347891706      318   36 6523
194 0.025    0.94 0.96749729 0.9612313 0.337191875      271   30 6570
195 0.025    0.95 0.97399783 0.9687017 0.376834874      219   24 6622
196 0.025    0.96 0.97833153 0.9741113 0.453423543      181   20 6660
197 0.025    0.97 0.98374865 0.9802937 0.497520294      138   15 6703
198 0.025    0.98 0.99241603 0.9875064 0.203108198       90    7 6751
199 0.025    0.99 0.99566631 0.9920144 0.258062753       58    4 6783
200 0.025    1.00 1.00000000 1.0000000 0.000000000        0    0 6841
201 0.050    0.01 0.09992862 0.0951829 0.536357502     5764 1261  599
202 0.050    0.02 0.12705211 0.1209428 0.465740639     5602 1223  761
203 0.050    0.03 0.15274804 0.1448995 0.378879666     5452 1187  911
204 0.050    0.04 0.17416131 0.1664091 0.411665730     5315 1157 1048
205 0.050    0.05 0.19557459 0.1846986 0.262383855     5203 1127 1160
206 0.050    0.06 0.21341899 0.2005410 0.196035184     5105 1102 1258
207 0.050    0.07 0.22412562 0.2153529 0.397286825     5005 1087 1358
208 0.050    0.08 0.24411135 0.2315817 0.232837047     4907 1059 1456
209 0.050    0.09 0.25838687 0.2461360 0.253609905     4814 1039 1549
210 0.050    0.10 0.27623126 0.2592736 0.117297788     4737 1014 1626
211 0.050    0.11 0.29264811 0.2753735 0.117380454     4635  991 1728
212 0.050    0.12 0.30549607 0.2881247 0.120349147     4554  973 1809
213 0.050    0.13 0.31120628 0.2982998 0.256746802     4483  965 1880
214 0.050    0.14 0.32334047 0.3082174 0.186113556     4423  948 1940
215 0.050    0.15 0.33404711 0.3212262 0.269755303     4337  933 2026
216 0.050    0.16 0.34475375 0.3323029 0.288439154     4266  918 2097
217 0.050    0.17 0.35831549 0.3444101 0.238447564     4191  899 2172
218 0.050    0.18 0.36902213 0.3563885 0.289215960     4113  884 2250
219 0.050    0.19 0.37758744 0.3633436 0.232563024     4071  872 2292
220 0.050    0.20 0.39186296 0.3733900 0.121498999     4013  852 2350
221 0.050    0.21 0.40328337 0.3858836 0.147754421     3932  836 2431
222 0.050    0.22 0.41256246 0.3956723 0.162134895     3869  823 2494
223 0.050    0.23 0.41970021 0.4045595 0.212986535     3810  813 2553
224 0.050    0.24 0.42683797 0.4149923 0.335014558     3739  803 2624
225 0.050    0.25 0.44039971 0.4234930 0.166103227     3692  784 2671
226 0.050    0.26 0.44967880 0.4328954 0.170458284     3632  771 2731
227 0.050    0.27 0.45538901 0.4434570 0.335374286     3558  763 2805
228 0.050    0.28 0.46823697 0.4545337 0.267766743     3490  745 2873
229 0.050    0.29 0.47394718 0.4645801 0.455098711     3420  737 2943
230 0.050    0.30 0.48394004 0.4733385 0.396240839     3366  723 2997
231 0.050    0.31 0.49393291 0.4841577 0.435855979     3296  709 3067
232 0.050    0.32 0.49964311 0.4945904 0.697774774     3223  701 3140
233 0.050    0.33 0.51249108 0.5038640 0.494040940     3169  683 3194
234 0.050    0.34 0.51962884 0.5117208 0.532239836     3118  673 3245
235 0.050    0.35 0.52748037 0.5204791 0.582393042     3061  662 3302
236 0.050    0.36 0.53319058 0.5278207 0.678014568     3012  654 3351
237 0.050    0.37 0.54104211 0.5350335 0.639425610     2967  643 3396
238 0.050    0.38 0.54817987 0.5421175 0.635870301     2922  633 3441
239 0.050    0.39 0.55817273 0.5508758 0.564024717     2868  619 3495
240 0.050    0.40 0.56388294 0.5580886 0.650768104     2820  611 3543
241 0.050    0.41 0.57102070 0.5659454 0.693867572     2769  601 3594
242 0.050    0.42 0.57815846 0.5739310 0.746223055     2717  591 3646
243 0.050    0.43 0.59172020 0.5829469 0.480348663     2666  572 3697
244 0.050    0.44 0.60171306 0.5914477 0.404617196     2614  558 3749
245 0.050    0.45 0.61099215 0.5999485 0.367105109     2561  545 3802
246 0.050    0.46 0.62098501 0.6079341 0.282357624     2513  531 3850
247 0.050    0.47 0.62740899 0.6159196 0.343972549     2460  522 3903
248 0.050    0.48 0.63311920 0.6239052 0.449656394     2406  514 3957
249 0.050    0.49 0.64596717 0.6322772 0.252927374     2359  496 4004
250 0.050    0.50 0.65096360 0.6385884 0.300976201     2317  489 4046
251 0.050    0.51 0.65738758 0.6455435 0.320765667     2272  480 4091
252 0.050    0.52 0.66880799 0.6534003 0.190997053     2227  464 4136
253 0.050    0.53 0.67880086 0.6625451 0.164463531     2170  450 4193
254 0.050    0.54 0.68665239 0.6700155 0.152281333     2123  439 4240
255 0.050    0.55 0.69950036 0.6789026 0.073067345     2072  421 4291
256 0.050    0.56 0.70521056 0.6863730 0.099582819     2022  413 4341
257 0.050    0.57 0.71377587 0.6946162 0.091421894     1970  401 4393
258 0.050    0.58 0.72019986 0.7022154 0.110977280     1920  392 4443
259 0.050    0.59 0.72733762 0.7108449 0.141148315     1863  382 4500
260 0.050    0.60 0.73304782 0.7174137 0.160657826     1820  374 4543
261 0.050    0.61 0.74232691 0.7246265 0.108432492     1777  361 4586
262 0.050    0.62 0.74946467 0.7317105 0.104490975     1732  351 4631
263 0.050    0.63 0.75517488 0.7396960 0.154198097     1678  343 4685
264 0.050    0.64 0.76017131 0.7465224 0.206456589     1632  336 4731
265 0.050    0.65 0.76730906 0.7545080 0.231894566     1580  326 4783
266 0.050    0.66 0.77587438 0.7613344 0.168918101     1539  314 4824
267 0.050    0.67 0.78586724 0.7690623 0.106597918     1493  300 4870
268 0.050    0.68 0.79514632 0.7774343 0.084521366     1441  287 4922
269 0.050    0.69 0.80585296 0.7856775 0.045840434     1392  272 4971
270 0.050    0.70 0.81084939 0.7921175 0.061177074     1349  265 5014
271 0.050    0.71 0.81513205 0.7980422 0.084835463     1309  259 5054
272 0.050    0.72 0.82084226 0.8070582 0.159470580     1247  251 5116
273 0.050    0.73 0.82940757 0.8143998 0.119216924     1202  239 5161
274 0.050    0.74 0.83511777 0.8207110 0.129931598     1161  231 5202
275 0.050    0.75 0.84653819 0.8274086 0.039980904     1125  215 5238
276 0.050    0.76 0.85082084 0.8339773 0.066966323     1080  209 5283
277 0.050    0.77 0.85438972 0.8414477 0.154276959     1027  204 5336
278 0.050    0.78 0.85867238 0.8482741 0.247170112      980  198 5383
279 0.050    0.79 0.86224126 0.8571613 0.576782468      916  193 5447
280 0.050    0.80 0.87080657 0.8642452 0.453903036      873  181 5490
281 0.050    0.81 0.87580300 0.8691396 0.439427254      842  174 5521
282 0.050    0.82 0.87937188 0.8760948 0.714024692      793  169 5570
283 0.050    0.83 0.88722341 0.8824060 0.566968365      755  158 5608
284 0.050    0.84 0.89364739 0.8898764 0.652040174      706  149 5657
285 0.050    0.85 0.90292648 0.8973467 0.476776280      661  136 5702
286 0.050    0.86 0.91220557 0.9048171 0.321852750      616  123 5747
287 0.050    0.87 0.92219843 0.9128027 0.185283729      568  109 5795
288 0.050    0.88 0.92862241 0.9188563 0.154232704      530  100 5833
289 0.050    0.89 0.93504640 0.9264554 0.192151290      480   91 5883
290 0.050    0.90 0.94004283 0.9339258 0.337700882      429   84 5934
291 0.050    0.91 0.94932191 0.9406234 0.144462327      390   71 5973
292 0.050    0.92 0.95431834 0.9479650 0.264290480      340   64 6023
293 0.050    0.93 0.95860100 0.9544049 0.446701200      296   58 6067
294 0.050    0.94 0.96431121 0.9612313 0.559753571      251   50 6112
295 0.050    0.95 0.97216274 0.9687017 0.461069645      204   39 6159
296 0.050    0.96 0.97644540 0.9741113 0.606701938      168   33 6195
297 0.050    0.97 0.98286938 0.9802937 0.509225035      129   24 6234
298 0.050    0.98 0.99286224 0.9875064 0.062776234       87   10 6276
299 0.050    0.99 0.99571734 0.9920144 0.120100978       56    6 6307
300 0.050    1.00 1.00000000 1.0000000 0.000000000        0    0 6363
301 0.075    0.01 0.09909400 0.0951829 0.554472984     5434 1591  564
302 0.075    0.02 0.12627407 0.1209428 0.459160577     5282 1543  716
303 0.075    0.03 0.15175538 0.1448995 0.371982356     5141 1498  857
304 0.075    0.04 0.17440544 0.1664091 0.322094223     5014 1458  984
305 0.075    0.05 0.19535674 0.1846986 0.201144238     4909 1421 1089
306 0.075    0.06 0.21234428 0.2005410 0.168942598     4816 1391 1182
307 0.075    0.07 0.22423556 0.2153529 0.317202711     4722 1370 1276
308 0.075    0.08 0.24462061 0.2315817 0.148247935     4632 1334 1366
309 0.075    0.09 0.25821065 0.2461360 0.190605327     4543 1310 1455
310 0.075    0.10 0.27859570 0.2592736 0.037786339     4477 1274 1521
311 0.075    0.11 0.29558324 0.2753735 0.032941280     4382 1244 1616
312 0.075    0.12 0.31030578 0.2881247 0.020789787     4309 1218 1689
313 0.075    0.13 0.31936580 0.2982998 0.029864193     4246 1202 1752
314 0.075    0.14 0.33012458 0.3082174 0.025154526     4188 1183 1810
315 0.075    0.15 0.34201586 0.3212262 0.035754225     4108 1162 1890
316 0.075    0.16 0.35277463 0.3323029 0.040442903     4041 1143 1957
317 0.075    0.17 0.36466591 0.3444101 0.044469761     3968 1122 2030
318 0.075    0.18 0.37599094 0.3563885 0.053774135     3895 1102 2103
319 0.075    0.19 0.38335221 0.3633436 0.049893359     3854 1089 2144
320 0.075    0.20 0.39694224 0.3733900 0.021446167     3800 1065 2198
321 0.075    0.21 0.40883352 0.3858836 0.025998038     3724 1044 2274
322 0.075    0.22 0.41789354 0.3956723 0.031951969     3664 1028 2334
323 0.075    0.23 0.42525481 0.4045595 0.046762322     3608 1015 2390
324 0.075    0.24 0.43374858 0.4149923 0.073041859     3542 1000 2456
325 0.075    0.25 0.44563986 0.4234930 0.034379074     3497  979 2501
326 0.075    0.26 0.45469989 0.4328954 0.037825952     3440  963 2558
327 0.075    0.27 0.46206116 0.4434570 0.077860938     3371  950 2627
328 0.075    0.28 0.47338618 0.4545337 0.074578051     3305  930 2693
329 0.075    0.29 0.47961495 0.4645801 0.157313838     3238  919 2760
330 0.075    0.30 0.48810872 0.4733385 0.165355628     3185  904 2813
331 0.075    0.31 0.49830125 0.4841577 0.184822102     3119  886 2879
332 0.075    0.32 0.50453001 0.4945904 0.355778027     3049  875 2949
333 0.075    0.33 0.51642129 0.5038640 0.240500972     2998  854 3000
334 0.075    0.34 0.52321631 0.5117208 0.283510719     2949  842 3049
335 0.075    0.35 0.53057758 0.5204791 0.347544055     2894  829 3104
336 0.075    0.36 0.53624009 0.5278207 0.435847378     2847  819 3151
337 0.075    0.37 0.54303511 0.5350335 0.459367803     2803  807 3195
338 0.075    0.38 0.54983012 0.5421175 0.475862857     2760  795 3238
339 0.075    0.39 0.55832390 0.5508758 0.491005234     2707  780 3291
340 0.075    0.40 0.56398641 0.5580886 0.588814287     2661  770 3337
341 0.075    0.41 0.57021518 0.5659454 0.700549908     2611  759 3387
342 0.075    0.42 0.57757644 0.5739310 0.745110126     2562  746 3436
343 0.075    0.43 0.59003398 0.5829469 0.509410199     2514  724 3484
344 0.075    0.44 0.59966025 0.5914477 0.440559910     2465  707 3533
345 0.075    0.45 0.60928652 0.5999485 0.376858646     2416  690 3582
346 0.075    0.46 0.61891280 0.6079341 0.294892497     2371  673 3627
347 0.075    0.47 0.62514156 0.6159196 0.379563091     2320  662 3678
348 0.075    0.48 0.63080408 0.6239052 0.513763378     2268  652 3730
349 0.075    0.49 0.64156285 0.6322772 0.372038863     2222  633 3776
350 0.075    0.50 0.64665912 0.6385884 0.438311011     2182  624 3816
351 0.075    0.51 0.65232163 0.6455435 0.516219394     2138  614 3860
352 0.075    0.52 0.66251416 0.6534003 0.374964874     2095  596 3903
353 0.075    0.53 0.67044168 0.6625451 0.441393250     2038  582 3960
354 0.075    0.54 0.67893545 0.6700155 0.379825970     1995  567 4003
355 0.075    0.55 0.69082673 0.6789026 0.233233458     1947  546 4051
356 0.075    0.56 0.69648924 0.6863730 0.310915768     1899  536 4099
357 0.075    0.57 0.70554926 0.6946162 0.268911368     1851  520 4147
358 0.075    0.58 0.71121178 0.7022154 0.362281192     1802  510 4196
359 0.075    0.59 0.71913930 0.7108449 0.398191830     1749  496 4249
360 0.075    0.60 0.72650057 0.7174137 0.349866061     1711  483 4287
361 0.075    0.61 0.73499434 0.7246265 0.280411022     1670  468 4328
362 0.075    0.62 0.74065685 0.7317105 0.349862094     1625  458 4373
363 0.075    0.63 0.74688562 0.7396960 0.451732984     1574  447 4424
364 0.075    0.64 0.75084938 0.7465224 0.656706354     1528  440 4470
365 0.075    0.65 0.75707814 0.7545080 0.799440115     1477  429 4521
366 0.075    0.66 0.76557191 0.7613344 0.657373188     1439  414 4559
367 0.075    0.67 0.77576444 0.7690623 0.466468877     1397  396 4601
368 0.075    0.68 0.78539071 0.7774343 0.377792036     1349  379 4649
369 0.075    0.69 0.79558324 0.7856775 0.262214373     1303  361 4695
370 0.075    0.70 0.80124575 0.7921175 0.297334739     1263  351 4735
371 0.075    0.71 0.80690827 0.7980422 0.306697819     1227  341 4771
372 0.075    0.72 0.81483579 0.8070582 0.363852953     1171  327 4827
373 0.075    0.73 0.82276331 0.8143998 0.320364804     1128  313 4870
374 0.075    0.74 0.83069083 0.8207110 0.226810674     1093  299 4905
375 0.075    0.75 0.84144960 0.8274086 0.081740205     1060  280 4938
376 0.075    0.76 0.84881087 0.8339773 0.061538939     1022  267 4976
377 0.075    0.77 0.85277463 0.8414477 0.148284380      971  260 5027
378 0.075    0.78 0.85730464 0.8482741 0.243702454      926  252 5072
379 0.075    0.79 0.86070215 0.8571613 0.656215424      863  246 5135
380 0.075    0.80 0.86806342 0.8642452 0.621700693      821  233 5177
381 0.075    0.81 0.87259343 0.8691396 0.653063769      791  225 5207
382 0.075    0.82 0.87655719 0.8760948 0.979245547      744  218 5254
383 0.075    0.83 0.88448471 0.8824060 0.789843458      709  204 5289
384 0.075    0.84 0.89354473 0.8898764 0.605130648      667  188 5331
385 0.075    0.85 0.90203851 0.8973467 0.487366893      624  173 5374
386 0.075    0.86 0.91166478 0.9048171 0.284845402      583  156 5415
387 0.075    0.87 0.92015855 0.9128027 0.230674257      536  141 5462
388 0.075    0.88 0.92695357 0.9188563 0.171232211      501  129 5497
389 0.075    0.89 0.93488109 0.9264554 0.135845382      456  115 5542
390 0.075    0.90 0.94054360 0.9339258 0.222756128      408  105 5590
391 0.075    0.91 0.94847112 0.9406234 0.125917208      370   91 5628
392 0.075    0.92 0.95413364 0.9479650 0.205154508      323   81 5675
393 0.075    0.93 0.95809740 0.9544049 0.434562515      280   74 5718
394 0.075    0.94 0.96545866 0.9612313 0.328628922      240   61 5758
395 0.075    0.95 0.97168743 0.9687017 0.458027414      193   50 5805
396 0.075    0.96 0.97734994 0.9741113 0.373552370      161   40 5837
397 0.075    0.97 0.98357871 0.9802937 0.301767917      124   29 5874
398 0.075    0.98 0.99207248 0.9875064 0.065244852       83   14 5915
399 0.075    0.99 0.99603624 0.9920144 0.044604773       55    7 5943
400 0.075    1.00 1.00000000 1.0000000 0.000000000        0    0 5998
401 0.100    0.01 0.10172745 0.0951829 0.251541338     5153 1872  527
402 0.100    0.02 0.12859885 0.1209428 0.224772854     5009 1816  671
403 0.100    0.03 0.15067179 0.1448995 0.401554792     4869 1770  811
404 0.100    0.04 0.17226488 0.1664091 0.420953637     4747 1725  933
405 0.100    0.05 0.19337812 0.1846986 0.245733752     4649 1681 1031
406 0.100    0.06 0.20873321 0.2005410 0.289137943     4558 1649 1122
407 0.100    0.07 0.22120921 0.2153529 0.465864298     4469 1623 1211
408 0.100    0.08 0.24088292 0.2315817 0.251605081     4384 1582 1296
409 0.100    0.09 0.25287908 0.2461360 0.420380197     4296 1557 1384
410 0.100    0.10 0.27063340 0.2592736 0.175645103     4231 1520 1449
411 0.100    0.11 0.28838772 0.2753735 0.126939031     4143 1483 1537
412 0.100    0.12 0.30230326 0.2881247 0.100454355     4073 1454 1607
413 0.100    0.13 0.31094050 0.2982998 0.147995959     4012 1436 1668
414 0.100    0.14 0.32101727 0.3082174 0.146571411     3956 1415 1724
415 0.100    0.15 0.33205374 0.3212262 0.226210953     3878 1392 1802
416 0.100    0.16 0.34404990 0.3323029 0.192288029     3817 1367 1863
417 0.100    0.17 0.35700576 0.3444101 0.165192932     3750 1340 1930
418 0.100    0.18 0.36804223 0.3563885 0.203385050     3680 1317 2000
419 0.100    0.19 0.37428023 0.3633436 0.235223306     3639 1304 2041
420 0.100    0.20 0.38819578 0.3733900 0.108007801     3590 1275 2090
421 0.100    0.21 0.40115163 0.3858836 0.099421156     3520 1248 2160
422 0.100    0.22 0.40930902 0.3956723 0.143680416     3461 1231 2219
423 0.100    0.23 0.41698656 0.4045595 0.185077221     3408 1215 2272
424 0.100    0.24 0.42706334 0.4149923 0.199992419     3348 1194 2332
425 0.100    0.25 0.43857965 0.4234930 0.108781463     3306 1170 2374
426 0.100    0.26 0.44721689 0.4328954 0.129302542     3251 1152 2429
427 0.100    0.27 0.45729367 0.4434570 0.144082279     3190 1131 2490
428 0.100    0.28 0.46833013 0.4545337 0.146194674     3127 1108 2553
429 0.100    0.29 0.47600768 0.4645801 0.231216032     3065 1092 2615
430 0.100    0.30 0.48464491 0.4733385 0.236818328     3015 1074 2665
431 0.100    0.31 0.49520154 0.4841577 0.248562506     2953 1052 2727
432 0.100    0.32 0.50239923 0.4945904 0.419097224     2887 1037 2793
433 0.100    0.33 0.51487524 0.5038640 0.250218177     2841 1011 2839
434 0.100    0.34 0.52159309 0.5117208 0.303717786     2794  997 2886
435 0.100    0.35 0.52927063 0.5204791 0.360924755     2742  981 2938
436 0.100    0.36 0.53502879 0.5278207 0.456289970     2697  969 2983
437 0.100    0.37 0.54174664 0.5350335 0.488505868     2655  955 3025
438 0.100    0.38 0.54798464 0.5421175 0.546625882     2613  942 3067
439 0.100    0.39 0.55566219 0.5508758 0.625662969     2561  926 3119
440 0.100    0.40 0.56190019 0.5580886 0.701085575     2518  913 3162
441 0.100    0.41 0.56861804 0.5659454 0.793344405     2471  899 3209
442 0.100    0.42 0.57533589 0.5739310 0.899937212     2423  885 3257
443 0.100    0.43 0.58685221 0.5829469 0.691547958     2377  861 3303
444 0.100    0.44 0.59740883 0.5914477 0.534476484     2333  839 3347
445 0.100    0.45 0.60700576 0.5999485 0.457658170     2287  819 3393
446 0.100    0.46 0.61660269 0.6079341 0.356816689     2245  799 3435
447 0.100    0.47 0.62236084 0.6159196 0.496189466     2195  787 3485
448 0.100    0.48 0.62859885 0.6239052 0.623625460     2146  774 3534
449 0.100    0.49 0.63915547 0.6322772 0.462465703     2103  752 3577
450 0.100    0.50 0.64491363 0.6385884 0.498996567     2066  740 3614
451 0.100    0.51 0.65067179 0.6455435 0.585462553     2024  728 3656
452 0.100    0.52 0.66074856 0.6534003 0.425320096     1984  707 3696
453 0.100    0.53 0.66842610 0.6625451 0.524290811     1929  691 3751
454 0.100    0.54 0.67658349 0.6700155 0.472575717     1888  674 3792
455 0.100    0.55 0.68809981 0.6789026 0.305868210     1843  650 3837
456 0.100    0.56 0.69385797 0.6863730 0.404599868     1797  638 3883
457 0.100    0.57 0.70393474 0.6946162 0.292769467     1754  617 3926
458 0.100    0.58 0.71065259 0.7022154 0.338688676     1709  603 3971
459 0.100    0.59 0.71833013 0.7108449 0.393690779     1658  587 4022
460 0.100    0.60 0.72552783 0.7174137 0.350618014     1622  572 4058
461 0.100    0.61 0.73512476 0.7246265 0.220319207     1586  552 4094
462 0.100    0.62 0.74232246 0.7317105 0.211508187     1546  537 4134
463 0.100    0.63 0.74904031 0.7396960 0.268126664     1498  523 4182
464 0.100    0.64 0.75383877 0.7465224 0.385261743     1455  513 4225
465 0.100    0.65 0.76007678 0.7545080 0.508709681     1406  500 4274
466 0.100    0.66 0.76823417 0.7613344 0.404351299     1370  483 4310
467 0.100    0.67 0.77735125 0.7690623 0.308028914     1329  464 4351
468 0.100    0.68 0.78550864 0.7774343 0.314789572     1281  447 4399
469 0.100    0.69 0.79462572 0.7856775 0.257361714     1236  428 4444
470 0.100    0.70 0.80134357 0.7921175 0.237236618     1200  414 4480
471 0.100    0.71 0.80662188 0.7980422 0.267547255     1165  403 4515
472 0.100    0.72 0.81477927 0.8070582 0.311606500     1112  386 4568
473 0.100    0.73 0.82293666 0.8143998 0.254699012     1072  369 4608
474 0.100    0.74 0.83061420 0.8207110 0.178776325     1039  353 4641
475 0.100    0.75 0.84117083 0.8274086 0.056152120     1009  331 4671
476 0.100    0.76 0.84740883 0.8339773 0.058472325      971  318 4709
477 0.100    0.77 0.85412668 0.8414477 0.069121141      927  304 4753
478 0.100    0.78 0.85892514 0.8482741 0.121410753      884  294 4796
479 0.100    0.79 0.86468330 0.8571613 0.266670746      827  282 4853
480 0.100    0.80 0.87188100 0.8642452 0.249150531      787  267 4893
481 0.100    0.81 0.87571977 0.8691396 0.315668632      757  259 4923
482 0.100    0.82 0.88003839 0.8760948 0.548526558      712  250 4968
483 0.100    0.83 0.88723608 0.8824060 0.446933199      678  235 5002
484 0.100    0.84 0.89539347 0.8898764 0.368260037      637  218 5043
485 0.100    0.85 0.90403071 0.8973467 0.257126090      597  200 5083
486 0.100    0.86 0.91458733 0.9048171 0.083049008      561  178 5119
487 0.100    0.87 0.92322457 0.9128027 0.054075150      517  160 5163
488 0.100    0.88 0.92946257 0.9188563 0.042738871      483  147 5197
489 0.100    0.89 0.93809981 0.9264554 0.019707563      442  129 5238
490 0.100    0.90 0.94337812 0.9339258 0.047779282      395  118 5285
491 0.100    0.91 0.95009597 0.9406234 0.037059512      357  104 5323
492 0.100    0.92 0.95681382 0.9479650 0.038563047      314   90 5366
493 0.100    0.93 0.96113244 0.9544049 0.096940512      273   81 5407
494 0.100    0.94 0.96833013 0.9612313 0.057914836      235   66 5445
495 0.100    0.95 0.97408829 0.9687017 0.114664768      189   54 5491
496 0.100    0.96 0.97936660 0.9741113 0.091866390      158   43 5522
497 0.100    0.97 0.98464491 0.9802937 0.114389160      121   32 5559
498 0.100    0.98 0.99184261 0.9875064 0.049033925       80   17 5600
499 0.100    0.99 0.99568138 0.9920144 0.039873584       53    9 5627
500 0.100    1.00 1.00000000 1.0000000 0.000000000        0    0 5680
    Dboth
1      53
2      66
3      83
4      92
5     103
6     114
7     120
8     132
9     140
10    150
11    157
12    164
13    168
14    174
15    177
16    184
17    192
18    195
19    200
20    206
21    213
22    213
23    217
24    220
25    226
26    227
27    231
28    237
29    239
30    243
31    245
32    247
33    257
34    261
35    264
36    267
37    270
38    273
39    280
40    282
41    285
42    287
43    291
44    297
45    303
46    308
47    310
48    313
49    320
50    323
51    326
52    333
53    337
54    339
55    346
56    348
57    353
58    357
59    360
60    362
61    370
62    372
63    375
64    378
65    383
66    385
67    390
68    393
69    397
70    399
71    399
72    402
73    404
74    405
75    408
76    408
77    411
78    412
79    414
80    416
81    418
82    419
83    421
84    424
85    427
86    429
87    432
88    437
89    439
90    443
91    446
92    447
93    450
94    454
95    456
96    459
97    462
98    466
99    467
100   470
101    99
102   125
103   151
104   169
105   193
106   212
107   221
108   243
109   260
110   280
111   288
112   297
113   302
114   312
115   318
116   331
117   343
118   352
119   362
120   371
121   382
122   389
123   395
124   401
125   415
126   424
127   430
128   439
129   446
130   454
131   463
132   469
133   482
134   489
135   497
136   504
137   508
138   513
139   525
140   531
141   537
142   544
143   552
144   561
145   572
146   582
147   588
148   593
149   605
150   611
151   617
152   629
153   635
154   642
155   654
156   658
157   667
158   673
159   681
160   688
161   699
162   707
163   711
164   716
165   725
166   733
167   741
168   753
169   761
170   766
171   768
172   772
173   781
174   785
175   792
176   795
177   798
178   803
179   805
180   811
181   816
182   818
183   823
184   829
185   838
186   849
187   859
188   866
189   870
190   876
191   883
192   884
193   887
194   893
195   899
196   903
197   908
198   916
199   919
200   923
201   140
202   178
203   214
204   244
205   274
206   299
207   314
208   342
209   362
210   387
211   410
212   428
213   436
214   453
215   468
216   483
217   502
218   517
219   529
220   549
221   565
222   578
223   588
224   598
225   617
226   630
227   638
228   656
229   664
230   678
231   692
232   700
233   718
234   728
235   739
236   747
237   758
238   768
239   782
240   790
241   800
242   810
243   829
244   843
245   856
246   870
247   879
248   887
249   905
250   912
251   921
252   937
253   951
254   962
255   980
256   988
257  1000
258  1009
259  1019
260  1027
261  1040
262  1050
263  1058
264  1065
265  1075
266  1087
267  1101
268  1114
269  1129
270  1136
271  1142
272  1150
273  1162
274  1170
275  1186
276  1192
277  1197
278  1203
279  1208
280  1220
281  1227
282  1232
283  1243
284  1252
285  1265
286  1278
287  1292
288  1301
289  1310
290  1317
291  1330
292  1337
293  1343
294  1351
295  1362
296  1368
297  1377
298  1391
299  1395
300  1401
301   175
302   223
303   268
304   308
305   345
306   375
307   396
308   432
309   456
310   492
311   522
312   548
313   564
314   583
315   604
316   623
317   644
318   664
319   677
320   701
321   722
322   738
323   751
324   766
325   787
326   803
327   816
328   836
329   847
330   862
331   880
332   891
333   912
334   924
335   937
336   947
337   959
338   971
339   986
340   996
341  1007
342  1020
343  1042
344  1059
345  1076
346  1093
347  1104
348  1114
349  1133
350  1142
351  1152
352  1170
353  1184
354  1199
355  1220
356  1230
357  1246
358  1256
359  1270
360  1283
361  1298
362  1308
363  1319
364  1326
365  1337
366  1352
367  1370
368  1387
369  1405
370  1415
371  1425
372  1439
373  1453
374  1467
375  1486
376  1499
377  1506
378  1514
379  1520
380  1533
381  1541
382  1548
383  1562
384  1578
385  1593
386  1610
387  1625
388  1637
389  1651
390  1661
391  1675
392  1685
393  1692
394  1705
395  1716
396  1726
397  1737
398  1752
399  1759
400  1766
401   212
402   268
403   314
404   359
405   403
406   435
407   461
408   502
409   527
410   564
411   601
412   630
413   648
414   669
415   692
416   717
417   744
418   767
419   780
420   809
421   836
422   853
423   869
424   890
425   914
426   932
427   953
428   976
429   992
430  1010
431  1032
432  1047
433  1073
434  1087
435  1103
436  1115
437  1129
438  1142
439  1158
440  1171
441  1185
442  1199
443  1223
444  1245
445  1265
446  1285
447  1297
448  1310
449  1332
450  1344
451  1356
452  1377
453  1393
454  1410
455  1434
456  1446
457  1467
458  1481
459  1497
460  1512
461  1532
462  1547
463  1561
464  1571
465  1584
466  1601
467  1620
468  1637
469  1656
470  1670
471  1681
472  1698
473  1715
474  1731
475  1753
476  1766
477  1780
478  1790
479  1802
480  1817
481  1825
482  1834
483  1849
484  1866
485  1884
486  1906
487  1924
488  1937
489  1955
490  1966
491  1980
492  1994
493  2003
494  2018
495  2030
496  2041
497  2052
498  2067
499  2075
500  2084
enrichment.plotter(gene.hic.filt, "weighted_Z.ALLvar.C", "adj.P.Val", "FDR for Weighted p-val Combine of Hi-C Contacts Overlapping Gene, Chimp")
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Version Author Date
6f6db11 Ittai Eres 2019-04-23

Version Author Date
6f6db11 Ittai Eres 2019-04-23

Version Author Date
6f6db11 Ittai Eres 2019-04-23

Version Author Date
6f6db11 Ittai Eres 2019-04-23
    DEFDR DHICFDR   prop.obs   prop.exp      chisq.p Dneither   DE DHiC
1   0.010    0.01 0.10503282 0.09139992 0.3376883752     6659  409  663
2   0.010    0.02 0.12910284 0.11633886 0.4225611847     6476  398  846
3   0.010    0.03 0.15536105 0.13857822 0.3170457095     6315  386 1007
4   0.010    0.04 0.17505470 0.15876077 0.3594262762     6167  377 1155
5   0.010    0.05 0.19037199 0.17688649 0.4742604326     6033  370 1289
6   0.010    0.06 0.20787746 0.19346960 0.4576880960     5912  362 1410
7   0.010    0.07 0.21881838 0.20825299 0.6072828039     5802  357 1520
8   0.010    0.08 0.24726477 0.22445044 0.2513366381     5689  344 1633
9   0.010    0.09 0.26695842 0.23961949 0.1754838932     5580  335 1742
10  0.010    0.10 0.28884026 0.25414578 0.0890336591     5477  325 1845
11  0.010    0.11 0.29978118 0.26867207 0.1356922508     5369  320 1953
12  0.010    0.12 0.31072210 0.28242705 0.1830628185     5267  315 2055
13  0.010    0.13 0.31728665 0.29155418 0.2322629940     5199  312 2123
14  0.010    0.14 0.32822757 0.30003857 0.1926537543     5138  307 2184
15  0.010    0.15 0.34354486 0.31147962 0.1405806378     5056  300 2266
16  0.010    0.16 0.35448578 0.32202083 0.1390372873     4979  295 2343
17  0.010    0.17 0.36980306 0.33243347 0.0897432077     4905  288 2417
18  0.010    0.18 0.38293217 0.34567425 0.0938327616     4808  282 2514
19  0.010    0.19 0.39606127 0.35338732 0.0552837229     4754  276 2568
20  0.010    0.20 0.40262582 0.36290012 0.0766746132     4683  273 2639
21  0.010    0.21 0.41137856 0.37446973 0.1029851050     4597  269 2725
22  0.010    0.22 0.41356674 0.38513948 0.2158459187     4515  268 2807
23  0.010    0.23 0.42231947 0.39478082 0.2332279961     4444  264 2878
24  0.010    0.24 0.43326039 0.40416506 0.2086438299     4376  259 2946
25  0.010    0.25 0.44201313 0.41174958 0.1915601706     4321  255 3001
26  0.010    0.26 0.44857768 0.42126237 0.2419414634     4250  252 3072
27  0.010    0.27 0.46389497 0.43141792 0.1626488057     4178  245 3144
28  0.010    0.28 0.47264770 0.44183057 0.1872273308     4101  241 3221
29  0.010    0.29 0.47921225 0.45262887 0.2591645149     4020  238 3302
30  0.010    0.30 0.48577681 0.46149891 0.3054886276     3954  235 3368
31  0.010    0.31 0.49671772 0.47114025 0.2798017537     3884  230 3438
32  0.010    0.32 0.49890591 0.48168145 0.4768798802     3803  229 3519
33  0.010    0.33 0.51203501 0.49145134 0.3903319775     3733  223 3589
34  0.010    0.34 0.52078775 0.50096413 0.4091465727     3663  219 3659
35  0.010    0.35 0.53172867 0.51009127 0.3651946162     3597  214 3725
36  0.010    0.36 0.53610503 0.51690449 0.4246422859     3546  212 3776
37  0.010    0.37 0.54266958 0.52526032 0.4715767160     3484  209 3838
38  0.010    0.38 0.54923414 0.53130222 0.4571865380     3440  206 3882
39  0.010    0.39 0.56017505 0.54017226 0.4031582705     3376  201 3946
40  0.010    0.40 0.56236324 0.54801388 0.5572971573     3316  200 4006
41  0.010    0.41 0.57768053 0.55739812 0.3946355546     3250  193 4072
42  0.010    0.42 0.58205689 0.56433989 0.4600893487     3198  191 4124
43  0.010    0.43 0.59299781 0.57269572 0.3922344189     3138  186 4184
44  0.010    0.44 0.60612691 0.58233706 0.3105696715     3069  180 4253
45  0.010    0.45 0.61925602 0.59107854 0.2248045496     3007  174 4315
46  0.010    0.46 0.63019694 0.59917727 0.1784537697     2949  169 4373
47  0.010    0.47 0.63676149 0.60663324 0.1903172226     2894  166 4428
48  0.010    0.48 0.64551422 0.61563183 0.1922240197     2828  162 4494
49  0.010    0.49 0.66083151 0.62218794 0.0879120952     2784  155 4538
50  0.010    0.50 0.66520788 0.63002957 0.1198061717     2725  153 4597
51  0.010    0.51 0.66958425 0.63787119 0.1603858178     2666  151 4656
52  0.010    0.52 0.68708972 0.64507006 0.0594804376     2618  143 4704
53  0.010    0.53 0.69365427 0.65394010 0.0736391476     2552  140 4770
54  0.010    0.54 0.69584245 0.66113896 0.1176722503     2497  139 4825
55  0.010    0.55 0.71115974 0.67026610 0.0621218526     2433  132 4889
56  0.010    0.56 0.71553611 0.67656511 0.0743993099     2386  130 4936
57  0.010    0.57 0.72647702 0.68466384 0.0534855991     2328  125 4994
58  0.010    0.58 0.73085339 0.69250546 0.0752599954     2269  123 5053
59  0.010    0.59 0.73960613 0.70124695 0.0728176726     2205  119 5117
60  0.010    0.60 0.74179431 0.70728885 0.1056603673     2159  118 5163
61  0.010    0.61 0.75492341 0.71525903 0.0596703682     2103  112 5219
62  0.010    0.62 0.76586433 0.72207225 0.0357130947     2055  107 5267
63  0.010    0.63 0.77680525 0.73029952 0.0241547302     1996  102 5326
64  0.010    0.64 0.78336980 0.73736984 0.0245442076     1944   99 5378
65  0.010    0.65 0.79431072 0.74636843 0.0176646240     1879   94 5443
66  0.010    0.66 0.79868709 0.75279599 0.0221277930     1831   92 5491
67  0.010    0.67 0.81181619 0.76269443 0.0128635602     1760   86 5562
68  0.010    0.68 0.82056893 0.77027896 0.0099670456     1705   82 5617
69  0.010    0.69 0.82494530 0.77773493 0.0145238994     1649   80 5673
70  0.010    0.70 0.82932166 0.78377684 0.0173487619     1604   78 5718
71  0.010    0.71 0.82932166 0.78956164 0.0366040403     1559   78 5763
72  0.010    0.72 0.83588621 0.79778892 0.0423556194     1498   75 5824
73  0.010    0.73 0.84463895 0.80614475 0.0371012817     1437   71 5885
74  0.010    0.74 0.84901532 0.81244376 0.0452196964     1390   69 5932
75  0.010    0.75 0.85339168 0.81810001 0.0507776579     1348   67 5974
76  0.010    0.76 0.85776805 0.82568454 0.0718795486     1291   65 6031
77  0.010    0.77 0.86214442 0.83314051 0.0990644626     1235   63 6087
78  0.010    0.78 0.86870897 0.84021082 0.0993566097     1183   60 6139
79  0.010    0.79 0.87089716 0.84946651 0.2101619648     1112   59 6210
80  0.010    0.80 0.87746171 0.85743669 0.2328353480     1053   56 6269
81  0.010    0.81 0.88402626 0.86412135 0.2264239101     1004   53 6318
82  0.010    0.82 0.88840263 0.87157732 0.3001646528      948   51 6374
83  0.010    0.83 0.89059081 0.87736213 0.4149962135      904   50 6418
84  0.010    0.84 0.89715536 0.88494665 0.4427705343      848   47 6474
85  0.010    0.85 0.90153173 0.89253117 0.5737649100      791   45 6531
86  0.010    0.86 0.90809628 0.90011570 0.6128117703      735   42 6587
87  0.010    0.87 0.91247265 0.90898573 0.8545559062      668   40 6654
88  0.010    0.88 0.92341357 0.91489909 0.5578932964      627   35 6695
89  0.010    0.89 0.92778993 0.92196940 0.6978066395      574   33 6748
90  0.010    0.90 0.93216630 0.92955393 0.8959848860      517   31 6805
91  0.010    0.91 0.94091904 0.93726700 0.8161939282      461   27 6861
92  0.010    0.92 0.94310722 0.94575138 0.8801411598      396   26 6926
93  0.010    0.93 0.94529540 0.95192184 0.5687979545      349   25 6973
94  0.010    0.94 0.95404814 0.95963491 0.6149749278      293   21 7029
95  0.010    0.95 0.95842451 0.96657668 0.3868936899      241   19 7081
96  0.010    0.96 0.96936543 0.97261859 0.7706514562      199   14 7123
97  0.010    0.97 0.97374179 0.97891760 0.5312770376      152   12 7170
98  0.010    0.98 0.98249453 0.98675922 0.5410660675       95    8 7227
99  0.010    0.99 0.99124726 0.99190127 1.0000000000       59    4 7263
100 0.010    1.00 1.00000000 1.00000000 0.0000000000        0    0 7322
101 0.025    0.01 0.10652174 0.09139992 0.1022414223     6246  822  613
102 0.025    0.02 0.13586957 0.11633886 0.0557668528     6079  795  780
103 0.025    0.03 0.16195652 0.13857822 0.0327731811     5930  771  929
104 0.025    0.04 0.18152174 0.15876077 0.0495575525     5791  753 1068
105 0.025    0.05 0.20652174 0.17688649 0.0137880282     5673  730 1186
106 0.025    0.06 0.22608696 0.19346960 0.0087218186     5562  712 1297
107 0.025    0.07 0.23478261 0.20825299 0.0387171662     5455  704 1404
108 0.025    0.08 0.26086957 0.22445044 0.0054772352     5353  680 1506
109 0.025    0.09 0.28152174 0.23961949 0.0017492580     5254  661 1605
110 0.025    0.10 0.30326087 0.25414578 0.0003138105     5161  641 1698
111 0.025    0.11 0.30978261 0.26867207 0.0031146997     5054  635 1805
112 0.025    0.12 0.31847826 0.28242705 0.0108410311     4955  627 1904
113 0.025    0.13 0.32282609 0.29155418 0.0289622124     4888  623 1971
114 0.025    0.14 0.33152174 0.30003857 0.0291982132     4830  615 2029
115 0.025    0.15 0.34130435 0.31147962 0.0411114438     4750  606 2109
116 0.025    0.16 0.35760870 0.32202083 0.0154070309     4683  591 2176
117 0.025    0.17 0.37065217 0.33243347 0.0097848863     4614  579 2245
118 0.025    0.18 0.38586957 0.34567425 0.0070783533     4525  565 2334
119 0.025    0.19 0.39782609 0.35338732 0.0030153624     4476  554 2383
120 0.025    0.20 0.40434783 0.36290012 0.0059983621     4408  548 2451
121 0.025    0.21 0.41413043 0.37446973 0.0090350763     4327  539 2532
122 0.025    0.22 0.42065217 0.38513948 0.0202756405     4250  533 2609
123 0.025    0.23 0.42717391 0.39478082 0.0353153136     4181  527 2678
124 0.025    0.24 0.43913043 0.40416506 0.0234648277     4119  516 2740
125 0.025    0.25 0.44782609 0.41174958 0.0196918380     4068  508 2791
126 0.025    0.26 0.45760870 0.42126237 0.0191699522     4003  499 2856
127 0.025    0.27 0.46630435 0.43141792 0.0251012051     3932  491 2927
128 0.025    0.28 0.47282609 0.44183057 0.0476186975     3857  485 3002
129 0.025    0.29 0.48043478 0.45262887 0.0768598321     3780  478 3079
130 0.025    0.30 0.48913043 0.46149891 0.0792265659     3719  470 3140
131 0.025    0.31 0.50217391 0.47114025 0.0484888256     3656  458 3203
132 0.025    0.32 0.50869565 0.48168145 0.0870353956     3580  452 3279
133 0.025    0.33 0.51847826 0.49145134 0.0870496586     3513  443 3346
134 0.025    0.34 0.52826087 0.50096413 0.0839246595     3448  434 3411
135 0.025    0.35 0.53695652 0.51009127 0.0889763262     3385  426 3474
136 0.025    0.36 0.54239130 0.51690449 0.1068865871     3337  421 3522
137 0.025    0.37 0.54782609 0.52526032 0.1542919111     3277  416 3582
138 0.025    0.38 0.55434783 0.53130222 0.1452348496     3236  410 3623
139 0.025    0.39 0.56413043 0.54017226 0.1291215113     3176  401 3683
140 0.025    0.40 0.56847826 0.54801388 0.1960342484     3119  397 3740
141 0.025    0.41 0.58043478 0.55739812 0.1435203140     3057  386 3802
142 0.025    0.42 0.58804348 0.56433989 0.1313587128     3010  379 3849
143 0.025    0.43 0.59673913 0.57269572 0.1249114377     2953  371 3906
144 0.025    0.44 0.60434783 0.58233706 0.1597077394     2885  364 3974
145 0.025    0.45 0.61521739 0.59107854 0.1210747822     2827  354 4032
146 0.025    0.46 0.62608696 0.59917727 0.0822323694     2774  344 4085
147 0.025    0.47 0.63260870 0.60663324 0.0926307731     2722  338 4137
148 0.025    0.48 0.64021739 0.61563183 0.1103818477     2659  331 4200
149 0.025    0.49 0.65217391 0.62218794 0.0498139028     2619  320 4240
150 0.025    0.50 0.65978261 0.63002957 0.0506682696     2565  313 4294
151 0.025    0.51 0.66630435 0.63787119 0.0608702081     2510  307 4349
152 0.025    0.52 0.67934783 0.64507006 0.0227677123     2466  295 4393
153 0.025    0.53 0.68478261 0.65394010 0.0396519366     2402  290 4457
154 0.025    0.54 0.69239130 0.66113896 0.0361076054     2353  283 4506
155 0.025    0.55 0.70326087 0.67026610 0.0257654878     2292  273 4567
156 0.025    0.56 0.70760870 0.67656511 0.0351958650     2247  269 4612
157 0.025    0.57 0.71847826 0.68466384 0.0207257708     2194  259 4665
158 0.025    0.58 0.72282609 0.69250546 0.0371250676     2137  255 4722
159 0.025    0.59 0.73043478 0.70124695 0.0432284805     2076  248 4783
160 0.025    0.60 0.73804348 0.70728885 0.0319736801     2036  241 4823
161 0.025    0.61 0.74782609 0.71525903 0.0218983401     1983  232 4876
162 0.025    0.62 0.75978261 0.72207225 0.0073635084     1941  221 4918
163 0.025    0.63 0.76847826 0.73029952 0.0061582762     1885  213 4974
164 0.025    0.64 0.77282609 0.73736984 0.0103867197     1834  209 5025
165 0.025    0.65 0.78260870 0.74636843 0.0080447592     1773  200 5086
166 0.025    0.66 0.78804348 0.75279599 0.0093606034     1728  195 5131
167 0.025    0.67 0.80000000 0.76269443 0.0052507423     1662  184 5197
168 0.025    0.68 0.80978261 0.77027896 0.0027740471     1612  175 5247
169 0.025    0.69 0.81847826 0.77773493 0.0017890191     1562  167 5297
170 0.025    0.70 0.82391304 0.78377684 0.0018921480     1520  162 5339
171 0.025    0.71 0.82608696 0.78956164 0.0043531560     1477  160 5382
172 0.025    0.72 0.83152174 0.79778892 0.0076037103     1418  155 5441
173 0.025    0.73 0.84347826 0.80614475 0.0026458062     1364  144 5495
174 0.025    0.74 0.84782609 0.81244376 0.0039405563     1319  140 5540
175 0.025    0.75 0.85326087 0.81810001 0.0037473901     1280  135 5579
176 0.025    0.76 0.85760870 0.82568454 0.0075433433     1225  131 5634
177 0.025    0.77 0.86086957 0.83314051 0.0185122982     1170  128 5689
178 0.025    0.78 0.86956522 0.84021082 0.0110887842     1123  120 5736
179 0.025    0.79 0.87173913 0.84946651 0.0496682679     1053  118 5806
180 0.025    0.80 0.88152174 0.85743669 0.0296313608     1000  109 5859
181 0.025    0.81 0.88695652 0.86412135 0.0356072640      953  104 5906
182 0.025    0.82 0.89021739 0.87157732 0.0805986810      898  101 5961
183 0.025    0.83 0.89456522 0.87736213 0.1008916289      857   97 6002
184 0.025    0.84 0.90000000 0.88494665 0.1418704420      803   92 6056
185 0.025    0.85 0.90760870 0.89253117 0.1295549179      751   85 6108
186 0.025    0.86 0.91630435 0.90011570 0.0919076826      700   77 6159
187 0.025    0.87 0.92173913 0.90898573 0.1703085011      636   72 6223
188 0.025    0.88 0.92934783 0.91489909 0.1074586062      597   65 6262
189 0.025    0.89 0.93478261 0.92196940 0.1395033458      547   60 6312
190 0.025    0.90 0.94239130 0.92955393 0.1206984573      495   53 6364
191 0.025    0.91 0.94891304 0.93726700 0.1391395565      441   47 6418
192 0.025    0.92 0.95000000 0.94575138 0.5972349439      376   46 6483
193 0.025    0.93 0.95108696 0.95192184 0.9649046659      329   45 6530
194 0.025    0.94 0.95760870 0.95963491 0.8077328552      275   39 6584
195 0.025    0.95 0.96630435 0.96657668 1.0000000000      229   31 6630
196 0.025    0.96 0.97500000 0.97261859 0.7160115947      190   23 6669
197 0.025    0.97 0.97934783 0.97891760 1.0000000000      145   19 6714
198 0.025    0.98 0.98804348 0.98675922 0.8341835725       92   11 6767
199 0.025    0.99 0.99347826 0.99190127 0.7095390184       57    6 6802
200 0.025    1.00 1.00000000 1.00000000 0.0000000000        0    0 6859
201 0.050    0.01 0.10236220 0.09139992 0.1288949617     5814 1254  568
202 0.050    0.02 0.13027917 0.11633886 0.0804560429     5659 1215  723
203 0.050    0.03 0.15390122 0.13857822 0.0738837192     5519 1182  863
204 0.050    0.04 0.17465999 0.15876077 0.0792863848     5391 1153  991
205 0.050    0.05 0.19470293 0.17688649 0.0590199277     5278 1125 1104
206 0.050    0.06 0.21188261 0.19346960 0.0592814267     5173 1101 1209
207 0.050    0.07 0.22118826 0.20825299 0.2011959347     5071 1088 1311
208 0.050    0.08 0.24481031 0.22445044 0.0478964334     4978 1055 1404
209 0.050    0.09 0.26413744 0.23961949 0.0195108923     4887 1028 1495
210 0.050    0.10 0.28203293 0.25414578 0.0090753979     4799 1003 1583
211 0.050    0.11 0.29062276 0.26867207 0.0444179632     4698  991 1684
212 0.050    0.12 0.30136006 0.28242705 0.0886326326     4606  976 1776
213 0.050    0.13 0.30780243 0.29155418 0.1490807734     4544  967 1838
214 0.050    0.14 0.31710809 0.30003857 0.1323793399     4491  954 1891
215 0.050    0.15 0.32927702 0.31147962 0.1201919457     4419  937 1963
216 0.050    0.16 0.34144596 0.32202083 0.0921990292     4354  920 2028
217 0.050    0.17 0.35218325 0.33243347 0.0893868304     4288  905 2094
218 0.050    0.18 0.36649964 0.34567425 0.0757513837     4205  885 2177
219 0.050    0.19 0.37795276 0.35338732 0.0366445507     4161  869 2221
220 0.050    0.20 0.39012169 0.36290012 0.0211431931     4104  852 2278
221 0.050    0.21 0.39942734 0.37446973 0.0359590953     4027  839 2355
222 0.050    0.22 0.40873300 0.38513948 0.0488008222     3957  826 2425
223 0.050    0.23 0.41589120 0.39478082 0.0797856544     3892  816 2490
224 0.050    0.24 0.42734431 0.40416506 0.0549812681     3835  800 2547
225 0.050    0.25 0.43808160 0.41174958 0.0294184317     3791  785 2591
226 0.050    0.26 0.44810308 0.42126237 0.0268811722     3731  771 2651
227 0.050    0.27 0.45454545 0.43141792 0.0578137827     3661  762 2721
228 0.050    0.28 0.46313529 0.44183057 0.0817609506     3592  750 2790
229 0.050    0.29 0.46957767 0.45262887 0.1689975319     3517  741 2865
230 0.050    0.30 0.47816750 0.46149891 0.1769746257     3460  729 2922
231 0.050    0.31 0.49033644 0.47114025 0.1193948509     3402  712 2980
232 0.050    0.32 0.49606299 0.48168145 0.2468038564     3328  704 3054
233 0.050    0.33 0.50823193 0.49145134 0.1752389536     3269  687 3113
234 0.050    0.34 0.51753758 0.50096413 0.1808083653     3208  674 3174
235 0.050    0.35 0.52612742 0.51009127 0.1956005448     3149  662 3233
236 0.050    0.36 0.53042233 0.51690449 0.2771647792     3102  656 3280
237 0.050    0.37 0.53972799 0.52526032 0.2436277118     3050  643 3332
238 0.050    0.38 0.54760200 0.53130222 0.1874139554     3014  632 3368
239 0.050    0.39 0.55547602 0.54017226 0.2159084664     2956  621 3426
240 0.050    0.40 0.55905512 0.54801388 0.3757317781     2900  616 3482
241 0.050    0.41 0.56979241 0.55739812 0.3173236799     2842  601 3540
242 0.050    0.42 0.57551897 0.56433989 0.3678234340     2796  593 3586
243 0.050    0.43 0.58554044 0.57269572 0.2975951704     2745  579 3637
244 0.050    0.44 0.59484610 0.58233706 0.3092903020     2683  566 3699
245 0.050    0.45 0.60343593 0.59107854 0.3138544569     2627  554 3755
246 0.050    0.46 0.61488905 0.59917727 0.1960655591     2580  538 3802
247 0.050    0.47 0.62061560 0.60663324 0.2497720667     2530  530 3852
248 0.050    0.48 0.62848962 0.61563183 0.2889808436     2471  519 3911
249 0.050    0.49 0.63922691 0.62218794 0.1556853937     2435  504 3947
250 0.050    0.50 0.64566929 0.63002957 0.1915019713     2383  495 3999
251 0.050    0.51 0.65354331 0.63787119 0.1885583657     2333  484 4049
252 0.050    0.52 0.66499642 0.64507006 0.0914926271     2293  468 4089
253 0.050    0.53 0.67358626 0.65394010 0.0943015296     2236  456 4146
254 0.050    0.54 0.68002863 0.66113896 0.1061749514     2189  447 4193
255 0.050    0.55 0.69148175 0.67026610 0.0671288145     2134  431 4248
256 0.050    0.56 0.69792412 0.67656511 0.0639434548     2094  422 4288
257 0.050    0.57 0.70866142 0.68466384 0.0357806741     2046  407 4336
258 0.050    0.58 0.71438797 0.69250546 0.0542538934     1993  399 4389
259 0.050    0.59 0.72083035 0.70124695 0.0830467618     1934  390 4448
260 0.050    0.60 0.72727273 0.70728885 0.0750929841     1896  381 4486
261 0.050    0.61 0.73586256 0.71525903 0.0641390577     1846  369 4536
262 0.050    0.62 0.74588404 0.72207225 0.0307394228     1807  355 4575
263 0.050    0.63 0.75518969 0.73029952 0.0225476505     1756  342 4626
264 0.050    0.64 0.75876879 0.73736984 0.0484920464     1706  337 4676
265 0.050    0.65 0.76735863 0.74636843 0.0503686799     1648  325 4734
266 0.050    0.66 0.77165354 0.75279599 0.0767913857     1604  319 4778
267 0.050    0.67 0.78453830 0.76269443 0.0371560903     1545  301 4837
268 0.050    0.68 0.79241231 0.77027896 0.0326701562     1497  290 4885
269 0.050    0.69 0.80171797 0.77773493 0.0190376533     1452  277 4930
270 0.050    0.70 0.80672870 0.78377684 0.0235259619     1412  270 4970
271 0.050    0.71 0.81245526 0.78956164 0.0225260164     1375  262 5007
272 0.050    0.72 0.81961346 0.79778892 0.0274218770     1321  252 5061
273 0.050    0.73 0.82963493 0.80614475 0.0157502116     1270  238 5112
274 0.050    0.74 0.83464567 0.81244376 0.0209354623     1228  231 5154
275 0.050    0.75 0.84323550 0.81810001 0.0080382503     1196  219 5186
276 0.050    0.76 0.84753042 0.82568454 0.0194270217     1143  213 5239
277 0.050    0.77 0.85182534 0.83314051 0.0425275025     1091  207 5291
278 0.050    0.78 0.85898354 0.84021082 0.0380916492     1046  197 5336
279 0.050    0.79 0.86327845 0.84946651 0.1205316666      980  191 5402
280 0.050    0.80 0.87329993 0.85743669 0.0672457193      932  177 5450
281 0.050    0.81 0.87974230 0.86412135 0.0660534710      889  168 5493
282 0.050    0.82 0.88403722 0.87157732 0.1355228449      837  162 5545
283 0.050    0.83 0.89047960 0.87736213 0.1084607667      801  153 5581
284 0.050    0.84 0.89620616 0.88494665 0.1585929465      750  145 5632
285 0.050    0.85 0.90193271 0.89253117 0.2282199550      699  137 5683
286 0.050    0.86 0.90909091 0.90011570 0.2356540264      650  127 5732
287 0.050    0.87 0.91696492 0.90898573 0.2742209744      592  116 5790
288 0.050    0.88 0.92340730 0.91489909 0.2280803893      555  107 5827
289 0.050    0.89 0.92913386 0.92196940 0.2950207156      508   99 5874
290 0.050    0.90 0.93486042 0.92955393 0.4248773780      457   91 5925
291 0.050    0.91 0.94345025 0.93726700 0.3215188788      409   79 5973
292 0.050    0.92 0.94774517 0.94575138 0.7656858270      349   73 6033
293 0.050    0.93 0.94989263 0.95192184 0.7471679339      304   70 6078
294 0.050    0.94 0.95633500 0.95963491 0.5373439788      253   61 6129
295 0.050    0.95 0.96564066 0.96657668 0.8944112744      212   48 6170
296 0.050    0.96 0.97351467 0.97261859 0.8917549403      176   37 6206
297 0.050    0.97 0.97995705 0.97891760 0.8447918536      136   28 6246
298 0.050    0.98 0.98854689 0.98675922 0.6057459988       87   16 6295
299 0.050    0.99 0.99355762 0.99190127 0.5499684387       54    9 6328
300 0.050    1.00 1.00000000 1.00000000 0.0000000000        0    0 6382
301 0.075    0.01 0.10000000 0.09139992 0.1670912629     5475 1593  534
302 0.075    0.02 0.12598870 0.11633886 0.1619662765     5327 1547  682
303 0.075    0.03 0.14745763 0.13857822 0.2336288099     5192 1509  817
304 0.075    0.04 0.16892655 0.15876077 0.1954762458     5073 1471  936
305 0.075    0.05 0.18870056 0.17688649 0.1479987686     4967 1436 1042
306 0.075    0.06 0.20564972 0.19346960 0.1493716703     4868 1406 1141
307 0.075    0.07 0.21581921 0.20825299 0.3905374597     4771 1388 1238
308 0.075    0.08 0.23785311 0.22445044 0.1322477932     4684 1349 1325
309 0.075    0.09 0.25536723 0.23961949 0.0828621846     4597 1318 1412
310 0.075    0.10 0.27570621 0.25414578 0.0193135369     4520 1282 1489
311 0.075    0.11 0.28813559 0.26867207 0.0383266453     4429 1260 1580
312 0.075    0.12 0.30169492 0.28242705 0.0435141535     4346 1236 1663
313 0.075    0.13 0.31016949 0.29155418 0.0534932312     4290 1221 1719
314 0.075    0.14 0.31920904 0.30003857 0.0485056869     4240 1205 1769
315 0.075    0.15 0.33050847 0.31147962 0.0526572713     4171 1185 1838
316 0.075    0.16 0.34180791 0.32202083 0.0456973155     4109 1165 1900
317 0.075    0.17 0.35141243 0.33243347 0.0574596743     4045 1148 1964
318 0.075    0.18 0.36779661 0.34567425 0.0279349276     3971 1119 2038
319 0.075    0.19 0.37740113 0.35338732 0.0174819385     3928 1102 2081
320 0.075    0.20 0.38926554 0.36290012 0.0094149022     3875 1081 2134
321 0.075    0.21 0.39887006 0.37446973 0.0170625552     3802 1064 2207
322 0.075    0.22 0.40960452 0.38513948 0.0173705519     3738 1045 2271
323 0.075    0.23 0.41694915 0.39478082 0.0320916155     3676 1032 2333
324 0.075    0.24 0.42881356 0.40416506 0.0174643585     3624 1011 2385
325 0.075    0.25 0.43898305 0.41174958 0.0087583371     3583  993 2426
326 0.075    0.26 0.44971751 0.42126237 0.0063098747     3528  974 2481
327 0.075    0.27 0.45762712 0.43141792 0.0122169137     3463  960 2546
328 0.075    0.28 0.46553672 0.44183057 0.0239562038     3396  946 2613
329 0.075    0.29 0.47231638 0.45262887 0.0620185669     3324  934 2685
330 0.075    0.30 0.47966102 0.46149891 0.0860103346     3268  921 2741
331 0.075    0.31 0.49152542 0.47114025 0.0538831994     3214  900 2795
332 0.075    0.32 0.49717514 0.48168145 0.1450486385     3142  890 2867
333 0.075    0.33 0.50847458 0.49145134 0.1089491521     3086  870 2923
334 0.075    0.34 0.51751412 0.50096413 0.1193764162     3028  854 2981
335 0.075    0.35 0.52542373 0.51009127 0.1495494567     2971  840 3038
336 0.075    0.36 0.53050847 0.51690449 0.2019261349     2927  831 3082
337 0.075    0.37 0.53898305 0.52526032 0.1976181710     2877  816 3132
338 0.075    0.38 0.54576271 0.53130222 0.1738237005     2842  804 3167
339 0.075    0.39 0.55367232 0.54017226 0.2042600093     2787  790 3222
340 0.075    0.40 0.55875706 0.54801388 0.3143581248     2735  781 3274
341 0.075    0.41 0.56836158 0.55739812 0.3033087956     2679  764 3330
342 0.075    0.42 0.57457627 0.56433989 0.3365823758     2636  753 3373
343 0.075    0.43 0.58418079 0.57269572 0.2783583525     2588  736 3421
344 0.075    0.44 0.59322034 0.58233706 0.3035128967     2529  720 3480
345 0.075    0.45 0.60282486 0.59107854 0.2643447654     2478  703 3531
346 0.075    0.46 0.61299435 0.59917727 0.1861607480     2433  685 3576
347 0.075    0.47 0.61920904 0.60663324 0.2283454665     2386  674 3623
348 0.075    0.48 0.62655367 0.61563183 0.2951197233     2329  661 3680
349 0.075    0.49 0.63559322 0.62218794 0.1951091755     2294  645 3715
350 0.075    0.50 0.64237288 0.63002957 0.2317724209     2245  633 3764
351 0.075    0.51 0.64858757 0.63787119 0.2987154814     2195  622 3814
352 0.075    0.52 0.65875706 0.64507006 0.1799254538     2157  604 3852
353 0.075    0.53 0.66610169 0.65394010 0.2319591773     2101  591 3908
354 0.075    0.54 0.67231638 0.66113896 0.2705353083     2056  580 3953
355 0.075    0.55 0.68418079 0.67026610 0.1651189420     2006  559 4003
356 0.075    0.56 0.68983051 0.67656511 0.1840031679     1967  549 4042
357 0.075    0.57 0.70000000 0.68466384 0.1209422647     1922  531 4087
358 0.075    0.58 0.70508475 0.69250546 0.2021025773     1870  522 4139
359 0.075    0.59 0.71186441 0.70124695 0.2797641636     1814  510 4195
360 0.075    0.60 0.71920904 0.70728885 0.2208298780     1780  497 4229
361 0.075    0.61 0.72824859 0.71525903 0.1777119689     1734  481 4275
362 0.075    0.62 0.73672316 0.72207225 0.1247038493     1696  466 4313
363 0.075    0.63 0.74576271 0.73029952 0.1015523424     1648  450 4361
364 0.075    0.64 0.74915254 0.73736984 0.2109543728     1599  444 4410
365 0.075    0.65 0.75706215 0.74636843 0.2520280732     1543  430 4466
366 0.075    0.66 0.76214689 0.75279599 0.3142879392     1502  421 4507
367 0.075    0.67 0.77457627 0.76269443 0.1918505232     1447  399 4562
368 0.075    0.68 0.78305085 0.77027896 0.1552495188     1403  384 4606
369 0.075    0.69 0.79152542 0.77773493 0.1198974673     1360  369 4649
370 0.075    0.70 0.79717514 0.78377684 0.1272365815     1323  359 4686
371 0.075    0.71 0.80395480 0.78956164 0.0975061643     1290  347 4719
372 0.075    0.72 0.81242938 0.79778892 0.0870490519     1241  332 4768
373 0.075    0.73 0.82033898 0.80614475 0.0920754783     1190  318 4819
374 0.075    0.74 0.82711864 0.81244376 0.0775818707     1153  306 4856
375 0.075    0.75 0.83446328 0.81810001 0.0459967803     1122  293 4887
376 0.075    0.76 0.84180791 0.82568454 0.0456386778     1076  280 4933
377 0.075    0.77 0.84632768 0.83314051 0.0975673519     1026  272 4983
378 0.075    0.78 0.85367232 0.84021082 0.0851204322      984  259 5025
379 0.075    0.79 0.85762712 0.84946651 0.2916165607      919  252 5090
380 0.075    0.80 0.86779661 0.85743669 0.1676713288      875  234 5134
381 0.075    0.81 0.87401130 0.86412135 0.1795553551      834  223 5175
382 0.075    0.82 0.87853107 0.87157732 0.3398241684      784  215 5225
383 0.075    0.83 0.88587571 0.87736213 0.2296867363      752  202 5257
384 0.075    0.84 0.89378531 0.88494665 0.1992932072      707  188 5302
385 0.075    0.85 0.89943503 0.89253117 0.3061222944      658  178 5351
386 0.075    0.86 0.90847458 0.90011570 0.1972802380      615  162 5394
387 0.075    0.87 0.91525424 0.90898573 0.3191465048      558  150 5451
388 0.075    0.88 0.92146893 0.91489909 0.2807647897      523  139 5486
389 0.075    0.89 0.92824859 0.92196940 0.2845250215      480  127 5529
390 0.075    0.90 0.93502825 0.92955393 0.3314554009      433  115 5576
391 0.075    0.91 0.94237288 0.93726700 0.3410040744      386  102 5623
392 0.075    0.92 0.94915254 0.94575138 0.5098477978      332   90 5677
393 0.075    0.93 0.95197740 0.95192184 1.0000000000      289   85 5720
394 0.075    0.94 0.95988701 0.95963491 1.0000000000      243   71 5766
395 0.075    0.95 0.96723164 0.96657668 0.9209819917      202   58 5807
396 0.075    0.96 0.97570621 0.97261859 0.4106125519      170   43 5839
397 0.075    0.97 0.98192090 0.97891760 0.3646202237      132   32 5877
398 0.075    0.98 0.98926554 0.98675922 0.3517022313       84   19 5925
399 0.075    0.99 0.99435028 0.99190127 0.2472343305       53   10 5956
400 0.075    1.00 1.00000000 1.00000000 0.0000000000        0    0 6009
401 0.100    0.01 0.09894837 0.09139992 0.1748343926     5183 1885  504
402 0.100    0.02 0.12380497 0.11633886 0.2279107982     5041 1833  646
403 0.100    0.03 0.14388145 0.13857822 0.4329950509     4910 1791  777
404 0.100    0.04 0.16539197 0.15876077 0.3494461846     4798 1746  889
405 0.100    0.05 0.18546845 0.17688649 0.2421549063     4699 1704  988
406 0.100    0.06 0.20076482 0.19346960 0.3392965597     4602 1672 1085
407 0.100    0.07 0.21128107 0.20825299 0.7132995342     4509 1650 1178
408 0.100    0.08 0.23279159 0.22445044 0.2988935521     4428 1605 1259
409 0.100    0.09 0.25000000 0.23961949 0.2037479604     4346 1569 1341
410 0.100    0.10 0.26912046 0.25414578 0.0702155568     4273 1529 1414
411 0.100    0.11 0.28346080 0.26867207 0.0791130987     4190 1499 1497
412 0.100    0.12 0.29684512 0.28242705 0.0920164036     4111 1471 1576
413 0.100    0.13 0.30592734 0.29155418 0.0961854950     4059 1452 1628
414 0.100    0.14 0.31500956 0.30003857 0.0854983568     4012 1433 1675
415 0.100    0.15 0.32648184 0.31147962 0.0881328106     3947 1409 1740
416 0.100    0.16 0.34034417 0.32202083 0.0384152171     3894 1380 1793
417 0.100    0.17 0.35038241 0.33243347 0.0443224225     3834 1359 1853
418 0.100    0.18 0.36615679 0.34567425 0.0227881594     3764 1326 1923
419 0.100    0.19 0.37428298 0.35338732 0.0207995099     3721 1309 1966
420 0.100    0.20 0.38671128 0.36290012 0.0087306339     3673 1283 2014
421 0.100    0.21 0.39818356 0.37446973 0.0094700190     3607 1259 2080
422 0.100    0.22 0.40774379 0.38513948 0.0139500426     3544 1239 2143
423 0.100    0.23 0.41586998 0.39478082 0.0225016288     3486 1222 2201
424 0.100    0.24 0.42734226 0.40416506 0.0124036186     3437 1198 2250
425 0.100    0.25 0.43785851 0.41174958 0.0049251169     3400 1176 2287
426 0.100    0.26 0.44741874 0.42126237 0.0049872688     3346 1156 2341
427 0.100    0.27 0.45697897 0.43141792 0.0062384063     3287 1136 2400
428 0.100    0.28 0.46558317 0.44183057 0.0113139657     3224 1118 2463
429 0.100    0.29 0.47514340 0.45262887 0.0166675406     3160 1098 2527
430 0.100    0.30 0.48374761 0.46149891 0.0181882054     3109 1080 2578
431 0.100    0.31 0.49521989 0.47114025 0.0106219073     3058 1056 2629
432 0.100    0.32 0.50286807 0.48168145 0.0249207873     2992 1040 2695
433 0.100    0.33 0.51386233 0.49145134 0.0176700129     2939 1017 2748
434 0.100    0.34 0.52198853 0.50096413 0.0261638611     2882 1000 2805
435 0.100    0.35 0.53059273 0.51009127 0.0301387856     2829  982 2858
436 0.100    0.36 0.53537285 0.51690449 0.0510070766     2786  972 2901
437 0.100    0.37 0.54254302 0.52526032 0.0678824821     2736  957 2951
438 0.100    0.38 0.54875717 0.53130222 0.0649644977     2702  944 2985
439 0.100    0.39 0.55640535 0.54017226 0.0860321938     2649  928 3038
440 0.100    0.40 0.56261950 0.54801388 0.1225453597     2601  915 3086
441 0.100    0.41 0.57217973 0.55739812 0.1172961677     2548  895 3139
442 0.100    0.42 0.57743786 0.56433989 0.1653576931     2505  884 3182
443 0.100    0.43 0.58652008 0.57269572 0.1418148028     2459  865 3228
444 0.100    0.44 0.59703633 0.58233706 0.1167707562     2406  843 3281
445 0.100    0.45 0.60659656 0.59107854 0.0964186502     2358  823 3329
446 0.100    0.46 0.61663480 0.59917727 0.0601757813     2316  802 3371
447 0.100    0.47 0.62284895 0.60663324 0.0801960747     2271  789 3416
448 0.100    0.48 0.63049713 0.61563183 0.1077417725     2217  773 3470
449 0.100    0.49 0.63957935 0.62218794 0.0584293388     2185  754 3502
450 0.100    0.50 0.64674952 0.63002957 0.0678384877     2139  739 3548
451 0.100    0.51 0.65344168 0.63787119 0.0879289043     2092  725 3595
452 0.100    0.52 0.66300191 0.64507006 0.0479298582     2056  705 3631
453 0.100    0.53 0.66969407 0.65394010 0.0810463979     2001  691 3686
454 0.100    0.54 0.67543021 0.66113896 0.1122540945     1957  679 3730
455 0.100    0.55 0.68690249 0.67026610 0.0620663291     1910  655 3777
456 0.100    0.56 0.69263862 0.67656511 0.0701802594     1873  643 3814
457 0.100    0.57 0.70315488 0.68466384 0.0356152019     1832  621 3855
458 0.100    0.58 0.70936902 0.69250546 0.0539579893     1784  608 3903
459 0.100    0.59 0.71558317 0.70124695 0.0994416517     1729  595 3958
460 0.100    0.60 0.72275335 0.70728885 0.0734531159     1697  580 3990
461 0.100    0.61 0.73040153 0.71525903 0.0772991239     1651  564 4036
462 0.100    0.62 0.73852772 0.72207225 0.0528153685     1615  547 4072
463 0.100    0.63 0.74808795 0.73029952 0.0344041191     1571  527 4116
464 0.100    0.64 0.75239006 0.73736984 0.0723697620     1525  518 4162
465 0.100    0.65 0.76003824 0.74636843 0.0986781362     1471  502 4216
466 0.100    0.66 0.76577438 0.75279599 0.1141684973     1433  490 4254
467 0.100    0.67 0.77772467 0.76269443 0.0629078951     1381  465 4306
468 0.100    0.68 0.78537285 0.77027896 0.0588836109     1338  449 4349
469 0.100    0.69 0.79302103 0.77773493 0.0528692646     1296  433 4391
470 0.100    0.70 0.79923518 0.78377684 0.0479681019     1262  420 4425
471 0.100    0.71 0.80544933 0.78956164 0.0400109307     1230  407 4457
472 0.100    0.72 0.81405354 0.79778892 0.0328126782     1184  389 4503
473 0.100    0.73 0.82265774 0.80614475 0.0276536611     1137  371 4550
474 0.100    0.74 0.82887189 0.81244376 0.0265198093     1101  358 4586
475 0.100    0.75 0.83604207 0.81810001 0.0140933136     1072  343 4615
476 0.100    0.76 0.84273423 0.82568454 0.0177715158     1027  329 4660
477 0.100    0.77 0.84799235 0.83314051 0.0360351751      980  318 4707
478 0.100    0.78 0.85516252 0.84021082 0.0317172026      940  303 4747
479 0.100    0.79 0.86042065 0.84946651 0.1089546855      879  292 4808
480 0.100    0.80 0.86998088 0.85743669 0.0597391380      837  272 4850
481 0.100    0.81 0.87619503 0.86412135 0.0646686333      798  259 4889
482 0.100    0.82 0.88145315 0.87157732 0.1233524958      751  248 4936
483 0.100    0.83 0.88814532 0.87736213 0.0855161374      720  234 4967
484 0.100    0.84 0.89483748 0.88494665 0.1056436566      675  220 5012
485 0.100    0.85 0.90009560 0.89253117 0.2057770083      627  209 5060
486 0.100    0.86 0.90965583 0.90011570 0.0970444923      588  189 5099
487 0.100    0.87 0.91682600 0.90898573 0.1574532744      534  174 5153
488 0.100    0.88 0.92256214 0.91489909 0.1546570371      500  162 5187
489 0.100    0.89 0.93021033 0.92196940 0.1105122462      461  146 5226
490 0.100    0.90 0.93642447 0.92955393 0.1656624558      415  133 5272
491 0.100    0.91 0.94407266 0.93726700 0.1474335844      371  117 5316
492 0.100    0.92 0.95172084 0.94575138 0.1759466731      321  101 5366
493 0.100    0.93 0.95506692 0.95192184 0.4674320924      280   94 5407
494 0.100    0.94 0.96271511 0.95963491 0.4399803393      236   78 5451
495 0.100    0.95 0.96988528 0.96657668 0.3609463657      197   63 5490
496 0.100    0.96 0.97705545 0.97261859 0.1688109203      165   48 5522
497 0.100    0.97 0.98279159 0.97891760 0.1758839296      128   36 5559
498 0.100    0.98 0.98948375 0.98675922 0.2447468853       81   22 5606
499 0.100    0.99 0.99426386 0.99190127 0.2049974605       51   12 5636
500 0.100    1.00 1.00000000 1.00000000 0.0000000000        0    0 5687
    Dboth
1      48
2      59
3      71
4      80
5      87
6      95
7     100
8     113
9     122
10    132
11    137
12    142
13    145
14    150
15    157
16    162
17    169
18    175
19    181
20    184
21    188
22    189
23    193
24    198
25    202
26    205
27    212
28    216
29    219
30    222
31    227
32    228
33    234
34    238
35    243
36    245
37    248
38    251
39    256
40    257
41    264
42    266
43    271
44    277
45    283
46    288
47    291
48    295
49    302
50    304
51    306
52    314
53    317
54    318
55    325
56    327
57    332
58    334
59    338
60    339
61    345
62    350
63    355
64    358
65    363
66    365
67    371
68    375
69    377
70    379
71    379
72    382
73    386
74    388
75    390
76    392
77    394
78    397
79    398
80    401
81    404
82    406
83    407
84    410
85    412
86    415
87    417
88    422
89    424
90    426
91    430
92    431
93    432
94    436
95    438
96    443
97    445
98    449
99    453
100   457
101    98
102   125
103   149
104   167
105   190
106   208
107   216
108   240
109   259
110   279
111   285
112   293
113   297
114   305
115   314
116   329
117   341
118   355
119   366
120   372
121   381
122   387
123   393
124   404
125   412
126   421
127   429
128   435
129   442
130   450
131   462
132   468
133   477
134   486
135   494
136   499
137   504
138   510
139   519
140   523
141   534
142   541
143   549
144   556
145   566
146   576
147   582
148   589
149   600
150   607
151   613
152   625
153   630
154   637
155   647
156   651
157   661
158   665
159   672
160   679
161   688
162   699
163   707
164   711
165   720
166   725
167   736
168   745
169   753
170   758
171   760
172   765
173   776
174   780
175   785
176   789
177   792
178   800
179   802
180   811
181   816
182   819
183   823
184   828
185   835
186   843
187   848
188   855
189   860
190   867
191   873
192   874
193   875
194   881
195   889
196   897
197   901
198   909
199   914
200   920
201   143
202   182
203   215
204   244
205   272
206   296
207   309
208   342
209   369
210   394
211   406
212   421
213   430
214   443
215   460
216   477
217   492
218   512
219   528
220   545
221   558
222   571
223   581
224   597
225   612
226   626
227   635
228   647
229   656
230   668
231   685
232   693
233   710
234   723
235   735
236   741
237   754
238   765
239   776
240   781
241   796
242   804
243   818
244   831
245   843
246   859
247   867
248   878
249   893
250   902
251   913
252   929
253   941
254   950
255   966
256   975
257   990
258   998
259  1007
260  1016
261  1028
262  1042
263  1055
264  1060
265  1072
266  1078
267  1096
268  1107
269  1120
270  1127
271  1135
272  1145
273  1159
274  1166
275  1178
276  1184
277  1190
278  1200
279  1206
280  1220
281  1229
282  1235
283  1244
284  1252
285  1260
286  1270
287  1281
288  1290
289  1298
290  1306
291  1318
292  1324
293  1327
294  1336
295  1349
296  1360
297  1369
298  1381
299  1388
300  1397
301   177
302   223
303   261
304   299
305   334
306   364
307   382
308   421
309   452
310   488
311   510
312   534
313   549
314   565
315   585
316   605
317   622
318   651
319   668
320   689
321   706
322   725
323   738
324   759
325   777
326   796
327   810
328   824
329   836
330   849
331   870
332   880
333   900
334   916
335   930
336   939
337   954
338   966
339   980
340   989
341  1006
342  1017
343  1034
344  1050
345  1067
346  1085
347  1096
348  1109
349  1125
350  1137
351  1148
352  1166
353  1179
354  1190
355  1211
356  1221
357  1239
358  1248
359  1260
360  1273
361  1289
362  1304
363  1320
364  1326
365  1340
366  1349
367  1371
368  1386
369  1401
370  1411
371  1423
372  1438
373  1452
374  1464
375  1477
376  1490
377  1498
378  1511
379  1518
380  1536
381  1547
382  1555
383  1568
384  1582
385  1592
386  1608
387  1620
388  1631
389  1643
390  1655
391  1668
392  1680
393  1685
394  1699
395  1712
396  1727
397  1738
398  1751
399  1760
400  1770
401   207
402   259
403   301
404   346
405   388
406   420
407   442
408   487
409   523
410   563
411   593
412   621
413   640
414   659
415   683
416   712
417   733
418   766
419   783
420   809
421   833
422   853
423   870
424   894
425   916
426   936
427   956
428   974
429   994
430  1012
431  1036
432  1052
433  1075
434  1092
435  1110
436  1120
437  1135
438  1148
439  1164
440  1177
441  1197
442  1208
443  1227
444  1249
445  1269
446  1290
447  1303
448  1319
449  1338
450  1353
451  1367
452  1387
453  1401
454  1413
455  1437
456  1449
457  1471
458  1484
459  1497
460  1512
461  1528
462  1545
463  1565
464  1574
465  1590
466  1602
467  1627
468  1643
469  1659
470  1672
471  1685
472  1703
473  1721
474  1734
475  1749
476  1763
477  1774
478  1789
479  1800
480  1820
481  1833
482  1844
483  1858
484  1872
485  1883
486  1903
487  1918
488  1930
489  1946
490  1959
491  1975
492  1991
493  1998
494  2014
495  2029
496  2044
497  2056
498  2070
499  2080
500  2092
#Custom function for doing this for the paper:
pap.enrichment.plotter <- function(df, HiC_col, DE_col, xlab, xmax=0.3, i=c(0.01, 0.025, 0.05, 0.075, 0.1), k=seq(0.01, 1, 0.01), significance=FALSE, recip=FALSE){
  enrich.table <- data.frame(DEFDR = c(rep(i[1], 100), rep(i[2], 100), rep(i[3], 100), rep(i[4], 100), rep(i[5], 100)), DHICFDR=rep(k, 5), prop.obs=NA, prop.exp=NA, chisq.p=NA, Dneither=NA, DE=NA, DHiC=NA, Dboth=NA)
  for(de.FDR in i){
    for(hic.FDR in k){
      enrich.table[which(enrich.table$DEFDR==de.FDR&enrich.table$DHICFDR==hic.FDR), 3:9] <- prop.calculator(df[,DE_col], df[,HiC_col], de.FDR, hic.FDR)
    }
  }
  des.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=prop.obs, group=as.factor(DEFDR), color=as.factor(DEFDR))) +geom_line()+ geom_line(aes(y=prop.exp), linetype="dashed", size=0.5) + ggtitle("Enrichment of DC in DE Genes") + xlab(xlab) + ylab("Proportion of DE genes that are DC") + guides(color=guide_legend(title="FDR for DE Genes"))
  dhics.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dboth+DHiC), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + geom_line(aes(y=(((((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth)))*(Dneither+DE+DHiC+Dboth))/(DHiC+Dboth))), linetype="dashed") + ylab("Proportion of DC genes that are DE") +xlab(xlab) + ggtitle("Enrichment of DE in DC Genes") + coord_cartesian(xlim=c(0, xmax), ylim=c(0.05, 0.32)) + guides(color=FALSE)
  joint.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dneither+DE+DHiC+Dboth), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + ylab("Proportion of ALL Genes both DE & DHi-C") + xlab(xlab) + geom_line(aes(y=((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth))), linetype="dashed") + ggtitle("Enrichment of Joint DE & DHi-C in All Genes")
  chisq.p <- ggplot(data=enrich.table, aes(x=DHICFDR, y=-log10(chisq.p), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_point() + geom_hline(yintercept=-log10(0.05), color="red") + ggtitle("Chi-squared Test P-values") + xlab(xlab) + ylab("-log10(chi-squared p-values)") + coord_cartesian(xlim=c(0, xmax), ylim=c(0, 3.2)) + guides(color=guide_legend(title="DE FDR"))
  if(recip==TRUE){
      des.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=prop.obs, group=as.factor(DEFDR), color=as.factor(DEFDR))) +geom_line()+ geom_line(aes(y=prop.exp), linetype="dashed", size=0.5) + ggtitle("Enrichment of DE in DC Genes") + xlab(xlab) + ylab("Proportion of DC genes that are DE") + guides(color=guide_legend(title="FDR for DC Genes"))
  dhics.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dboth+DHiC), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + geom_line(aes(y=(((((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth)))*(Dneither+DE+DHiC+Dboth))/(DHiC+Dboth))), linetype="dashed") + ylab("Proportion of DE genes that are DC") +xlab(xlab) + ggtitle("Enrichment of DC in DE Genes") + coord_cartesian(xlim=c(0, xmax))  + guides(color=FALSE)
  joint.enriched <- ggplot(data=enrich.table, aes(x=DHICFDR, y=Dboth/(Dneither+DE+DHiC+Dboth), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_line() + ylab("Proportion of ALL Genes both DE & DHi-C") + xlab(xlab) + geom_line(aes(y=((DE+Dboth)/(Dneither+DE+DHiC+Dboth))*((DHiC+Dboth)/(Dneither+DE+DHiC+Dboth))), linetype="dashed") + ggtitle("Enrichment of Joint DE & DHi-C in All Genes")
  chisq.p <- ggplot(data=enrich.table, aes(x=DHICFDR, y=-log10(chisq.p), group=as.factor(DEFDR), color=as.factor(DEFDR))) + geom_point() + geom_hline(yintercept=-log10(0.05), color="red") + ggtitle("Chi-squared Test P-values") + xlab(xlab) + ylab("-log10(chi-squared p-values)") + coord_cartesian(xlim=c(0, xmax)) + guides(color=guide_legend(title="DC FDR"))
  }
if(significance==TRUE){
    return(chisq.p)
  }
    else{
      return(dhics.enriched)
    }
}

#FIG6
FIG6A <- pap.enrichment.plotter(gene.hic.filt, "min_FDR.H", "adj.P.Val", "Minimum FDR of Contacts", xmax=1) #FIG6A
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect
FIG6B <- pap.enrichment.plotter(gene.hic.filt, "min_FDR.H", "adj.P.Val", "Minimum FDR of Contacts", xmax=1, significance = TRUE) #FIG6B
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect
#FIG6C <- pap.enrichment.plotter(gene.hic.filt, "weighted_Z.ALLvar.H", "adj.P.Val", "FDR for Weighted P-val Combination", xmax=1) #FIG6C
#FIG6D <- pap.enrichment.plotter(gene.hic.filt, "weighted_Z.ALLvar.H", "adj.P.Val", "FDR for Weighted P-val Combination", xmax=1, significance = TRUE) #FIG6D
FIG6 <- plot_grid(FIG6A, FIG6B, labels=c("A", "B"), align="h", rel_widths=c(1, 1.2))
save_plot("~/Desktop/FIG6.tiff", FIG6, nrow=1, ncol=2) #Good again, but needs to be copied into photoshop to reduce size!

#FIGS20
FIGS20A <- pap.enrichment.plotter(gene.hic.filt, "adj.P.Val", "min_FDR.H",  "Minimum FDR of Genes", xmax=1, recip=TRUE) #FIGS20A
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect
FIGS20B <- pap.enrichment.plotter(gene.hic.filt, "adj.P.Val", "min_FDR.H",  "Minimum FDR of Genes", xmax=1, significance = TRUE, recip=TRUE) #FIGS20B
Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect

Warning in chisq.test(mytable): Chi-squared approximation may be incorrect
FIGS20 <- plot_grid(FIGS20A, FIGS20B, labels=c("A", "B"), align="h", rel_widths=c(1, 1.2))
save_plot("~/Desktop/FIGS20.png", FIGS20, nrow=1, ncol=2)

Now that I’ve seen some enrichment of differential contact (DC) in differential expression (DE) based on my linear modeling results from before, I would like to further quantify this effect. In order to do so, I now extract log2 observed/expected homer-normalized contact frequency values and RPKM expression values for each gene/bin set, so I can look at correlations of these values and assess their explanatory power.

Contact Frequency Extraction

In this section, I proceed to create a function in order to extract the Hi-C interaction frequency values for the different types of summaries I’ve made gene overlaps with above. This allows for operations to be performed separately utilizing different summaries of Hi-C contacts.

#Get a df with the H and C coordinates of the hits, and the IF values from homer. This subset df makes things easier to extract.
contacts <- data.frame(h1=data.filtered$H1, h2=data.filtered$H2, c1=data.filtered$C1, c2=data.filtered$C2, A_21792_HIC=data.filtered$`A-21792_norm`, B_28126_HIC=data.filtered$`B-28126_norm`, C_3649_HIC=data.filtered$`C-3649_norm`, D_40300_HIC=data.filtered$`D-40300_norm`, E_28815_HIC=data.filtered$`E-28815_norm`, F_28834_HIC=data.filtered$`F-28834_norm`, G_3624_HIC=data.filtered$`G-3624_norm`, H_3651_HIC=data.filtered$`H-3651_norm`, stringsAsFactors = FALSE)

#Now ensure first member of a pair is always lower than second:
newH1 <- as.numeric(gsub(".*-", "", contacts$h1))
newH2 <- as.numeric(gsub(".*-", "", contacts$h2))
lower.HID <- ifelse(newH1<newH2, contacts$h1, contacts$h2)
higher.HID2 <- ifelse(newH1<newH2, contacts$h2, contacts$h1)
contacts$hpair <- paste(lower.HID, higher.HID2, sep="_")

newC1 <- as.numeric(gsub(".*-", "", contacts$c1))
newC2 <- as.numeric(gsub(".*-", "", contacts$c2))
lower.CID <- ifelse(newC1<newC2, contacts$c1, contacts$c2)
higher.CID2 <- ifelse(newC1<newC2, contacts$c2, contacts$c1)
contacts$cpair <- paste(lower.CID, higher.CID2, sep="_")

#A function that takes a dataframe (like gene.hic.filt) and two columns from the dataframe to create a pair vector for the given interaction. First ensures the first bin in a pair is always lowest to make this easier. Then extracts the IF values for that vector from the contacts df created above. This provides me with the appropriate Hi-C data values for the different bin classes we're examining here, so that I can later test them with linear modeling to quantify their effect on expression.
IF.extractor <- function(dataframe, col1, col2, contacts, species, strand=FALSE){
  new1 <- as.numeric(gsub(".*-", "", dataframe[,col1]))
  if(strand==FALSE){#In the case where I'm not worried about strand, I just work with the second column selected.
    new2 <- as.numeric(gsub(".*-", "", dataframe[,col2]))
    lower1 <- ifelse(new1<new2, dataframe[,col1], dataframe[,col2])
    higher2 <- ifelse(new1<new2, dataframe[,col2], dataframe[,col1]) #Fix all the columns first
    if(species=="H"){ #Then depending on species create the pair column and merge to contact info.
      dataframe[,"hpair"] <- paste(lower1, higher2, sep="_")
      finaldf <- left_join(dataframe, contacts[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "hpair")], by="hpair")
    }
    else if(species=="C"){
      dataframe[,"cpair"] <- paste(lower1, higher2, sep="_")
      finaldf <- left_join(dataframe, contacts[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "cpair")], by="cpair")
    }
  }
  else if(strand==TRUE){#If dealing with upstream and downstream hits, need to do things separately for genes on the + and - strand.
    if(species=="H"){
      US <- ifelse(dataframe[,"Hstrand.H"]=="+", dataframe[,"US_bin.H"], dataframe[,"DS_bin.H"]) #Obtain upstream bins depending on strand.
      new2 <- as.numeric(gsub(".*-", "", US)) #Now rearrange the pairs to ensure regardless of stream we can find the pair (first mate lower coordinates than 2nd).
      lower1 <- ifelse(new1<new2, dataframe[,col1], US)
      higher2 <- ifelse(new1<new2, US, dataframe[,col1])
      dataframe[,"hpair"] <- paste(lower1, higher2, sep="_")
      dataframe[,"USFDR"] <- ifelse(dataframe[,"Hstrand.H"]=="+", dataframe[,"US_FDR.H"], dataframe[,"DS_FDR.H"])
      finaldf <- left_join(dataframe, contacts[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "hpair")], by="hpair")
    }
    else if(species=="C"){
      US <- ifelse(dataframe[,"Hstrand.C"]=="+", dataframe[,"US_bin.C"], dataframe[,"DS_bin.C"]) #Obtain upstream bins depending on strand.
      new2 <- as.numeric(gsub(".*-", "", US)) #Now rearrange the pairs to ensure regardless of stream we can find the pair (first mate lower coordinates than 2nd).
      lower1 <- ifelse(new1<new2, dataframe[,col1], US)
      higher2 <- ifelse(new1<new2, US, dataframe[,col1])
      dataframe[,"cpair"] <- paste(lower1, higher2, sep="_")
      dataframe[,"USFDR"] <- ifelse(dataframe[,"Hstrand.C"]=="+", dataframe[,"US_FDR.C"], dataframe[,"DS_FDR.C"])
      finaldf <- left_join(dataframe, contacts[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "cpair")], by="cpair")
    }
  }
  #before finally returning, remove rows where we don't have full Hi-C data.
  finaldf <- finaldf[complete.cases(finaldf[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC")]),]
  return(finaldf)
}

#Now I can use the IF.extractor function to make a number of different dataframes for actually testing different IF values with the RPKM expression values.
h_minFDR <- IF.extractor(gene.hic.filt, "HID", "min_FDR_bin.H", contacts, "H")
c_minFDR <- IF.extractor(gene.hic.filt, "CID", "min_FDR_bin.C", contacts, "C")
h_maxB <- IF.extractor(gene.hic.filt, "HID", "max_B_bin.H", contacts, "H")
c_maxB <- IF.extractor(gene.hic.filt, "CID", "max_B_bin.C", contacts, "C")
h_US <- IF.extractor(gene.hic.filt, "HID", "US_bin.H", contacts, "H", TRUE)
c_US <- IF.extractor(gene.hic.filt, "CID", "US_bin.C", contacts, "C", TRUE)

#Write these out so they can be permuted upon on midway2.
fwrite(h_minFDR, "data/old_mediation_permutations/HiC_covs/h_minFDR", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(c_minFDR, "data/old_mediation_permutations/HiC_covs/c_minFDR", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(h_maxB, "data/old_mediation_permutations/HiC_covs/h_maxB", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(c_maxB, "data/old_mediation_permutations/HiC_covs/c_maxB", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(h_US, "data/old_mediation_permutations/HiC_covs/h_US", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(c_US, "data/old_mediation_permutations/HiC_covs/c_US", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)

#Now the same thing, but subsetting down to ONLY the genes that show evidence for DE at 5% FDR.
h_minFDR_DE <- filter(h_minFDR, adj.P.Val<=0.05)
c_minFDR_DE <- filter(c_minFDR, adj.P.Val<=0.05)
h_maxB_DE <- filter(h_maxB, adj.P.Val<=0.05)
c_maxB_DE <- filter(c_maxB, adj.P.Val<=0.05)
h_US_DE <- filter(h_US, adj.P.Val<=0.05)
c_US_DE <- filter(c_US, adj.P.Val<=0.05)

fwrite(h_minFDR_DE, "data/old_mediation_permutations/HiC_covs/h_minFDR_DE", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(c_minFDR_DE, "data/old_mediation_permutations/HiC_covs/c_minFDR_DE", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(h_maxB_DE, "data/old_mediation_permutations/HiC_covs/h_maxB_DE", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(c_maxB_DE, "data/old_mediation_permutations/HiC_covs/c_maxB_DE", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(h_US_DE, "data/old_mediation_permutations/HiC_covs/h_US_DE", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)
fwrite(c_US_DE, "data/old_mediation_permutations/HiC_covs/c_US_DE", quote = FALSE, sep = "\t", na = "NA", col.names = TRUE)

Now I use these data frames and join each again on the RPKM table by genes, in order to obtain RPKM expression values for each gene-Hi-C bin set.

Merging contact frequency values with expression values.

In this next section I join each of the data frames created above on the RPKM table by genes, in order to have a merged table with expression values and contact frequencies for each gene-Hi-C bin set. I move then to explore correlations between the values.

#Join all of the previously-made Hi-C interaction frequency tables to the RPKM table by genes, to obtain RPKM values in concert with contact frequency values.
RPKM <- as.data.frame(weighted.data$E)
RPKM$genes <- rownames(RPKM)
hmin <- left_join(h_minFDR, RPKM, by="genes")
cmin <- left_join(c_minFDR, RPKM, by="genes")
hmaxB <- left_join(h_maxB, RPKM, by="genes")
cmaxB <- left_join(c_maxB, RPKM, by="genes")
hUS <- left_join(h_US, RPKM, by="genes")
cUS <- left_join(c_US, RPKM, by="genes")

#Get the same thing filtered for only DE genes.
hminDE <- filter(hmin, adj.P.Val<=0.05)
cminDE <- filter(cmin, adj.P.Val<=0.05)
hmaxBDE <- filter(hmaxB, adj.P.Val<=0.05)
cmaxBDE <- filter(cmaxB, adj.P.Val <=0.05)
hUSDE <- filter(hUS, adj.P.Val<=0.05)
cUSDE <- filter(cUS, adj.P.Val<=0.05)

hmin_noDE <- filter(hmin, adj.P.Val>0.05) #Pull out specific set of non-DE hits.

#Extract contacts and expression for the contact with the lowest FDR from linear modeling.
mycontacts <- hmin[,61:68]
myexprs <- hmin[,69:76]
DEcontacts <- hminDE[,61:68]
DEexprs <- hminDE[,69:76]
nonDEcontacts <- hmin_noDE[,61:68]
nonDEexprs <- hmin_noDE[,69:76]

#Extract contacts and expression stratified by mean interspecies expression quantiles.
quant1contactexpr <- filter(hmin, AveExpr<=quantile(hmin$AveExpr)[2]) %>% select(., A_21792_HIC, B_28126_HIC, C_3649_HIC, D_40300_HIC, E_28815_HIC, F_28834_HIC, G_3624_HIC, H_3651_HIC, "A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")
quant2contactexpr <- filter(hmin, AveExpr>quantile(hmin$AveExpr)[2]&AveExpr<=quantile(hmin$AveExpr)[3]) %>% select(., A_21792_HIC, B_28126_HIC, C_3649_HIC, D_40300_HIC, E_28815_HIC, F_28834_HIC, G_3624_HIC, H_3651_HIC, "A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")
quant3contactexpr <- filter(hmin, AveExpr>quantile(hmin$AveExpr)[3]&AveExpr<=quantile(hmin$AveExpr)[4]) %>% select(., A_21792_HIC, B_28126_HIC, C_3649_HIC, D_40300_HIC, E_28815_HIC, F_28834_HIC, G_3624_HIC, H_3651_HIC, "A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")
quant4contactexpr <- filter(hmin, AveExpr>quantile(hmin$AveExpr)[4]&AveExpr<=quantile(hmin$AveExpr)[5]) %>% select(., A_21792_HIC, B_28126_HIC, C_3649_HIC, D_40300_HIC, E_28815_HIC, F_28834_HIC, G_3624_HIC, H_3651_HIC, "A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")

#Function for calculating gene-wise correlations.
cor.calc <- function(hicdata, exprdata){
  cor.exp <- vector(length=nrow(hicdata))
  for(i in 1:nrow(hicdata)){
    cor.exp[i] <- cor(as.numeric(hicdata[i,]), as.numeric(exprdata[i,]))
  }
  return(cor.exp)
}

#Calculate correlations for different sets! I've commented out the species-specific calculations here because they just aren't that interesting. If you look at DE dynamics within each species you do NOT get a gorgeous bimodal as you do for across--looks more uniform and messy.
fullcors <- data.frame(cor=cor.calc(mycontacts, myexprs), type="all")
fullDEcors <- data.frame(cor=cor.calc(DEcontacts, DEexprs), type="DE")
fullnoDEcors <- data.frame(cor=cor.calc(nonDEcontacts, nonDEexprs), type="non-DE")
quant1cor <- data.frame(cor=cor.calc(quant1contactexpr[,1:8], quant1contactexpr[,9:16]), type="quant1")
quant2cor <- data.frame(cor=cor.calc(quant2contactexpr[,1:8], quant2contactexpr[,9:16]), type="quant2")
quant3cor <- data.frame(cor=cor.calc(quant3contactexpr[,1:8], quant3contactexpr[,9:16]), type="quant3")
quant4cor <- data.frame(cor=cor.calc(quant4contactexpr[,1:8], quant4contactexpr[,9:16]), type="quant4")
# humcors <- data.frame(cor=cor.calc(mycontacts[,c(1:2, 5:6)], myexprs[,c(1:2, 5:6)]), type="h_ALL")
# humDEcors <- data.frame(cor=cor.calc(DEcontacts[,c(1:2, 5:6)], DEexprs[,c(1:2, 5:6)]), type="h_DE")
# humnoDEcors <- data.frame(cor=cor.calc(nonDEcontacts[,c(1:2, 5:6)], nonDEexprs[,c(1:2, 5:6)]), type="h_non-DE")
# chimpcors <- data.frame(cor=cor.calc(mycontacts[,c(3:4, 7:8)], myexprs[,c(3:4, 7:8)]), type="c_ALL")
# chimpDEcors <- data.frame(cor=cor.calc(DEcontacts[,c(3:4, 7:8)], DEexprs[,c(3:4, 7:8)]), type="c_DE")
# chimpnoDEcors <- data.frame(cor=cor.calc(nonDEcontacts[,c(3:4, 7:8)], nonDEexprs[,c(3:4, 7:8)]), type="c_non-DE")

#Combine these dfs to plot in one gorgeous ggplot!
ggcors <- rbind(fullcors, fullDEcors, fullnoDEcors, quant1cor, quant2cor, quant3cor, quant4cor)#, humcors, humDEcors, humnoDEcors, chimpcors, chimpDEcors, chimpnoDEcors)

#First without the expression quantiles, then with.
ggplot(data=filter(ggcors, type=="all"|type=="DE"|type=="non-DE")) + stat_density(aes(x=cor, group=type, color=type, y=..scaled..), position="identity", geom="line") + ggtitle("Correlation b/t RPKM Expression and Hi-C Contact Frequency") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + scale_color_manual("Gene Set", values=c("red", "blue", "green"), labels=c("All genes", "DE genes", "non-DE genes"))

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=ggcors) + stat_density(aes(x=cor, group=type, color=type, y=..scaled..), position="identity", geom="line") + ggtitle("Correlation b/t RPKM Expression and Hi-C Contact Frequency") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + scale_color_manual("Gene Set", values=c("red", "blue", "green", "purple", "orange", "yellow", "brown"), labels=c("All genes", "DE genes", "non-DE genes", "expression.quant1", "expression.quant2", "expression.quant3", "expression.quant4"))

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=filter(ggcors, type=="DE"|type=="non-DE")) + stat_density(aes(x=cor, group=type, color=type, y=..scaled..), position="identity", geom="line") + ggtitle("Correlations between Expression and Hi-C Contact Frequency") + xlab("Pearson Correlations, Expression and Hi-C Contact Frequency") + ylab("Density") + scale_color_manual("Gene Set", values=c("red", "blue"), labels=c("DE genes", "non-DE genes")) + theme(plot.title=element_text(hjust=0.2))

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
###This looks great, showing strong bimodal distribution for the DE genes and broader distributions with a peak at 0 for the non-DE set and the full set. Also see no difference in terms of the distribution of correlations on individual sets of genes stratified by quantiles of expression (mean b/t species). Note that I've done that on just DE genes as well and see slightly shorter peaks on the bimodality for the middle quantiles of expression, which makes sense (extreme unlikely to be as severe b/t species). Also, to assess if this is legit at all, I now re-run this correlation analysis after permuting the Hi-C values. I shuffle sample IDs on a gene-by-gene basis to accomplish this:
cor.permuter <- function(hicdata, exprdata, nperm){
  result <- data.frame(cor=NA, type=rep(1:nperm, each=nrow(exprdata)))
  for(perm in 1:nperm){
    permute <- hicdata
    for(row in 1:nrow(hicdata)){
      permute[row,] <- sample(hicdata[row,])
    }
    myindices <- which(result$type==perm)
    result[myindices,1] <- cor.calc(permute, exprdata)
  }
  return(result)
}

#Just do it with 10 permutations to see the general effect quickly:
full.perm <- cor.permuter(mycontacts, myexprs, 10)
DE.perm <-  cor.permuter(DEcontacts, DEexprs, 10)
nonDE.perm <- cor.permuter(nonDEcontacts, nonDEexprs, 10)

#Now visualize.
#FIGS15
ggplot(data=filter(ggcors, type=="all"|type=="DE"|type=="non-DE")) + stat_density(aes(x=cor, group=type, color=type, y=..scaled..), position="identity", geom="line") + stat_density(data=full.perm, aes(x=cor, group=type), geom="line", linetype="dotted", position="identity") + stat_density(data=DE.perm, aes(x=cor, group=type), geom="line", linetype="dashed", position="identity") + stat_density(data=nonDE.perm, aes(x=cor, group=type), geom="line", linetype="twodash", position="identity") + ggtitle("Correlation b/t RPKM Expression and Hi-C Contact Frequency") + xlab("Pearson Correlations, RPKM Expression & Hi-C Contact Frequency") + ylab("Density") + scale_color_manual("Gene Set", values=c("red", "blue", "green"), labels=c("All genes", "DE genes", "non-DE genes")) + theme(plot.title=element_text(hjust=0.3))#FIGS15

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
#See that permuted datasets have a tighter correlation distribution with a strong peak at 0. Reassuring. In the future I will repeat this analysis on Midway2, running 10000 permutations to see the full range of permuted data possible.

####Deprecated, for use in species-specific analysis.
# plotfull <- data.frame(fullcors=fullcors, Hcors=humcors, Ccors=chimpcors)
# plotDE <- data.frame(fullcors=fullDEcors[,1], Hcors=humDEcors[,1], Ccors=chimpDEcors[,1])
# 
# ggplot(data=plotfull) + stat_density(aes(x=fullcors), geom="line") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + ggtitle("Correlations between Hi-C and Expression, all genes")
# ggplot(data=plotfull) + stat_density(aes(x=Hcors), geom="line") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + ggtitle("Correlations between Hi-C and Expression, all genes, Humans")
# ggplot(data=plotfull) + stat_density(aes(x=Ccors), geom="line") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + ggtitle("Correlations between Hi-C and Expression, all genes, Chimps")
# 
# ggplot(data=plotDE) + stat_density(aes(x=fullcors), geom="line") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + ggtitle("Correlations between Hi-C and Expression, DE genes")
# ggplot(data=plotDE) + stat_density(aes(x=Hcors), geom="line") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + ggtitle("Correlations between Hi-C and Expression, DE genes, Humans")
# ggplot(data=plotDE) + stat_density(aes(x=Ccors), geom="line") + xlab("Pearson Correlations b/t RPKM Expression and Hi-C Contact Frequency") + ylab("Density") + ggtitle("Correlations between Hi-C and Expression, DE genes, Chimps")

Now that I’ve seen some nice effects in the correlation between expression and contact for different sets of genes, and for permutations on those sets, I move to see what kind of quantitiative explanatory power differential contact (DC) might actually have for differential expression (DE).

How well does Hi-C data explain expression data?

In this next section I “regress out” the effect of Hi-C contacts from their overlapping genes’ RPKM expression values, comparing a linear model run on the base values to one run on the residuals of expression after regressing out Hi-C data. Comparing the p-values before and after this regression can give some sense of whether the DE is being driven by differential Hi-C contacts (DC).

###A function to calculate gene-wise correlations between Hi-C data and expression data, but for spearman correlations. Pearson correlation calculator function is in the chunk above.
cor.calc.spear <- function(hicdata, exprdata){
  cor.exp <- vector(length=nrow(hicdata))
  for(i in 1:nrow(hicdata)){
    cor.exp[i] <- cor(as.numeric(hicdata[i,]), as.numeric(exprdata[i,]), method="spearman")
  }
  return(cor.exp)
}

###A function to permute a Hi-C df by going gene-by-gene (row-by-row) and shuffling all sample IDs.
shuffler <- function(hicdata){
    for(row in 1:nrow(hicdata)){
      hicdata[row,] <- sample(hicdata[row,])
    }
    return(hicdata)
}

###A function that runs a linear model, both with and without Hi-C corrected expression values, and returns a dataframe of hit classes (DE or not before and after correction). Also spits back out p-values before and after correction, as well as correlations between Hi-C data and expression data. Since the former is a one-row data frame of 4 points and the latter is a 3-column data frame with the number of genes rows, returns a list.
lmcorrect <- function(voom.obj, exprs, cov_matrix, meta_df){
  mygenes <- cov_matrix$genes #Pull out the relevant genes here; used for subsetting the voom.obj in a bit.
  cov_matrix <- cov_matrix[, -9] #Remove genes from the cov matrix
  hic_present <- sapply(1:nrow(cov_matrix), function(i) !any(is.na(cov_matrix[i,]))) #First, remove any rows w/ missing Hi-C data.
  exprs <- data.matrix(exprs[hic_present,]) #Filter expression with this
  cov_matrix <- data.matrix(cov_matrix[hic_present,]) #Filter Hi-C data with this
  
  #Now, prepare to run the actual models. First run a model w/ Hi-C as a covariate to evaluate
  SP <- factor(meta_df$SP,levels = c("H","C"))
  design <- model.matrix(~0+SP)
  colnames(design) <- c("Human", "Chimp")
  resid_hic <- array(0, dim=c(nrow(exprs), ncol(cov_matrix))) #Initialize a dataframe for storing the residuals.
  for(i in 1:nrow(exprs)){#Loop through rows of the expression df, running linear modeling w/ Hi-C to obtain residuals.
   resid_hic[i,] <- lm(exprs[i,]~cov_matrix[i,])$resid 
  }
  
  mycon <- makeContrasts(HvC = Human-Chimp, levels = design)
  
  #Filter the voom object to only contain genes that had Hi-C information here.
  good.indices <- which(rownames(voom.obj$E) %in% mygenes)
  voom.obj <- voom.obj[good.indices,]
  
  #Now, replace the RPKM values in the voom object for after linear modeling with the residuals.
  voom.obj.after <- voom.obj
  voom.obj.after$E <- resid_hic
  
  lmFit(voom.obj, design=design) %>% eBayes(.) %>% contrasts.fit(., mycon) %>% eBayes(.) %>% topTable(., coef = 1, adjust.method = "BH", number = Inf, sort.by="none") -> fit_before
  lmFit(voom.obj.after, design=design) %>% eBayes(.) %>% contrasts.fit(., mycon) %>% eBayes(.) %>% topTable(., coef = 1, adjust.method = "BH", number = Inf, sort.by="none") -> fit_after

  result.DE.cats <- data.frame(DEneither=sum(fit_before$adj.P.Val>0.05&fit_after$adj.P.Val>0.05), DEbefore=sum(fit_before$adj.P.Val<=0.05&fit_after$adj.P.Val>0.05), DEafter=sum(fit_before$adj.P.Val>0.05&fit_after$adj.P.Val<=0.05), DEboth=sum(fit_before$adj.P.Val<=0.05&fit_after$adj.P.Val<=0.05))
  result.DE.stats <- data.frame(cor.pear=cor.calc(cov_matrix, exprs), cor.spear=cor.calc.spear(cov_matrix, exprs), pval.before=fit_before$adj.P.Val, pval.after=fit_after$adj.P.Val)
  result <- list("categories"=result.DE.cats, "stats"=result.DE.stats)
  return(result)
}

#Proceed to use the function on the different dataframes I've created with different sets of overlapping Hi-C contacts:
h_minFDR_pvals <- lmcorrect(weighted.data, hmin[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], hmin[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], meta.data)
c_minFDR_pvals <- lmcorrect(weighted.data, cmin[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], cmin[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], meta.data)
h_maxB_pvals <- lmcorrect(weighted.data, hmaxB[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], hmaxB[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], meta.data)
c_maxB_pvals <- lmcorrect(weighted.data, cmaxB[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], cmaxB[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], meta.data)
h_US_pvals <- lmcorrect(weighted.data, hUS[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], hUS[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], meta.data)
c_US_pvals <- lmcorrect(weighted.data, cUS[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], cUS[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], meta.data)

#I now proceed to visualize the difference in p-values for expression before and after "correcting" for the Hi-C data. I am hoping to see many hits in the bottom right quadrant of the following plots, indicating genes that showed up as DE before Hi-C correction, but not after. I also expect that p-values falling farther away from the null line of expectation for p-values being identical between models will have higher correlations, which I color here for the pearson correlation (results look similar for spearman).
ggplot(data=h_minFDR_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after), color=abs(cor.pear))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE before vs. after regressing out Hi-C contact frequency") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=h_minFDR_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE Before vs. After Regressing out Hi-C Contact Frequency") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression)") + theme(plot.title=element_text(hjust=1)) #Slightly cleaner, for MindBytes 2018 poster

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=h_maxB_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after), color=abs(cor.pear))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE before vs. after regressing out Hi-C max beta (H)") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=h_US_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after), color=abs(cor.spear))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE before vs. after regressing out Hi-C US bin FDR (H)") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=c_minFDR_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after), color=abs(cor.pear))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE before vs. after regressing out Hi-C min. FDR (C)") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=c_maxB_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after), color=abs(cor.pear))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE before vs. after regressing out Hi-C max beta (C)") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14
ggplot(data=c_US_pvals$stats, aes(x=-log10(pval.before), y=-log10(pval.after), color=abs(cor.pear))) + geom_point(size=0.01) + geom_hline(yintercept=-log10(0.05), color="red") + geom_vline(xintercept=-log10(0.05), color="red") + geom_abline(slope=1, intercept=0, color="green", linetype="dashed") + ggtitle("Evidence for DE before vs. after regressing out Hi-C US bin FDR (C)") + xlab("-log10(p-value of DE before Hi-C regression)") + ylab("-log10(p-value of DE after Hi-C regression")

Version Author Date
6f6db11 Ittai Eres 2019-04-23
a02a602 Ittai Eres 2019-03-14

Critically, here I see that “regressing out” Hi-C data and trying to model expression again moves many genes from being significantly differentially expressed (at FDR of 5%) to no longer showing differential expression. Seeing most of the hits in the bottom right corner of these visualizations is what confirms this. Reassuringly, I also see stronger correlations between RPKM expression values and normalized Hi-C interaction frequency values for points farther away from the diagonal green line of expectation. However, since this is not a statistical test, I have no assessment of significance. To accomplish this, I compare these results to running the same kind of analysis on permuted data in the next section.

Find the contacts and DE genes that are most highly correlated:

hmin_full <- cbind(hmin, h_minFDR_pvals$stats) %>% select(., genes, logFC, AveExpr, adj.P.Val, B, genepos.H, HID, min_FDR_bin.H, min_FDR_pval, min_FDR_B.H, genepos.C, CID, min_FDR_bin.C, min_FDR.C, min_FDR_B.C, "A_21792_HIC", "B_28126_HIC", C_3649_HIC, D_40300_HIC, E_28815_HIC, F_28834_HIC, G_3624_HIC, H_3651_HIC, "A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651", cor.pear, cor.spear)
hmin_ranked <- hmin_full[order(-hmin_full$cor.pear),] #Rank by correlation between contact and expression
hmin_ranked_DE <- filter(hmin_full, adj.P.Val<=0.05&min_FDR_pval<=0.05) #Subset to just DE genes and DC contacts.
hmin_final <- hmin_ranked_DE[complete.cases(hmin_ranked_DE),] #Get rid of NA rows.

#I am looking for a scenario where chimps have a contact with an enhancer-like element that strongly increases expression, and humans do not have that same contact, presumably because of a CTCF insulation site in between. Hence I want stronger contact leading to increased expression, so subset to only positive correlations between the two:
hmin_final <- filter(hmin_final, cor.pear>0)
hmin_final <- hmin_final[order(hmin_final$cor.pear, decreasing = T),]

#Get distances between promoter and contact that is DC:
hmin_final$Hdist <- hmin_final$genepos.H-as.numeric(gsub(".*-", "",hmin_final$min_FDR_bin.H))
hmin_final$Cdist <- hmin_final$genepos.C-as.numeric(gsub(".*-", "", hmin_final$min_FDR_bin.C))

#Subset down to only those that are 60kb apart in both species or less:
hmin_final <- filter(hmin_final, abs(Hdist)<=100000&abs(Cdist<=100000)&abs(Hdist)>=20000&abs(Cdist>=20000))

#Realistically, it will be easier to find the CTCF element in humans. This means I am looking for DC regions where the Beta is negative, and expression is lower in humans as a result of less contact than in chimps (same filtering, really).
hmin_final <- filter(hmin_final, min_FDR_B.H<0)

#Prepare a BED file of the contacts being made in this final DF to check between them for CTCF binding:
options(scipen=999)
myBED <- data.frame(hchr=gsub("-.*", "", hmin_final$min_FDR_bin.H), hgene=as.integer(gsub(".*-", "", hmin_final$HID)), hcontact=as.integer(gsub(".*-", "", hmin_final$min_FDR_bin.H)), cchr=gsub("-.*", "", hmin_final$min_FDR_bin.C), cgene=as.integer(gsub(".*-", "", hmin_final$CID)), ccontact=as.integer(gsub(".*-", "", hmin_final$min_FDR_bin.C)), geneID=hmin_final$genes, cor.pear=hmin_final$cor.pear, cor.spear=hmin_final$cor.spear)
myBED$hstart <- ifelse(myBED$hgene<myBED$hcontact, myBED$hgene, myBED$hcontact)
myBED$hend <- ifelse(myBED$hcontact>myBED$hgene, myBED$hcontact, myBED$hgene)
myBED$DE_beta <- hmin_final$logFC
myBED$DC_beta <- hmin_final$min_FDR_B.H
myBED$dist <- hmin_final$Hdist
#myBED <- as.data.frame(myBED)
fwrite(myBED, quote = FALSE, "/Users/ittaieres/Desktop/Insulator_Experiment/insulator.candidates.bed", sep="\t", row.names=F, col.names=F)
#write.table(as.matrix(myBED), quote=FALSE, "/Users/ittaieres/Desktop/Insulator_Experiment/insulator.candidates.bed", sep="\t", col.names=F, row.names=F)

candidates <- fread("/Users/ittaieres/Desktop/Insulator_Experiment/CTCF.filtered.candidates.bed", sep="\t", header=F, data.table=F)
candidates$ID <- paste(candidates$V1, candidates$V2, candidates$V3, sep="_")
myBED$ID <- paste(myBED$hchr, myBED$hstart, myBED$hend, sep="_")
final.merge <- left_join(candidates, myBED, by="ID")

#Write out human and chimp BED files for extracting FASTA sequences so I can check for CTCF motif.
human.coords <- select(final.merge, hchr, hstart, hend) #Sorted by earlier coords coming first. Need to do this sorting for chimp:
final.merge$cstart <- ifelse(final.merge$cgene<final.merge$ccontact, final.merge$cgene, final.merge$ccontact)
final.merge$cend <- ifelse(final.merge$ccontact>final.merge$cgene, final.merge$ccontact, final.merge$cgene)
chimp.coords <- select(final.merge, cchr, cstart, cend)

fwrite(human.coords, quote=F, "/Users/ittaieres/Desktop/Insulator_Experiment/human.CTCF.filtered.candidates.bed", sep="\t", row.names=F, col.names=F)
fwrite(chimp.coords, quote=F, "/Users/ittaieres/Desktop/Insulator_Experiment/chimp.CTCF.filtered.candidates.bed", sep="\t", row.names=F, col.names=F)

#Make an average RPKM file for the genes:
hmin_final$ave.expr.H <- rowMeans(select(hmin_final, "A-21792", "B-28126", "E-28815", "F-28834"))
hmin_final$ave.expr.C <- rowMeans(select(hmin_final, "C-3649", "D-40300", "G-3624", "H-3651"))
hgenes <- data.frame(chr=gsub("-.*", "", hmin_final$min_FDR_bin.H), hgene=as.integer(hmin_final$genepos.H), hgene.end=hmin_final$genepos.H+250, hexpr=hmin_final$ave.expr.H, cexpr=hmin_final$ave.expr.C)
cgenes <- data.frame(chr=gsub("-.*", "", hmin_final$min_FDR_bin.C), cgene=as.integer(hmin_final$genepos.C), cgene.end=hmin_final$genepos.C+250, cexpr=hmin_final$ave.expr.C, hexpr=hmin_final$ave.expr.H)
hgenes$cstart <- hgenes$hgene+250
hgenes$cend <- hgenes$hgene.end+250
cgenes$hstart <- cgenes$cgene+250
cgenes$hend <- cgenes$cgene.end+250

hgene.h.bedgraph <- select(hgenes, chr, hgene, hgene.end, hexpr)
hgene.c.bedgraph <- select(hgenes, chr, cstart, cend, cexpr)
cgene.c.bedgraph <- select(cgenes, chr, cgene, cgene.end, cexpr)
cgene.h.bedgraph <- select(cgenes, chr, hstart, hend, hexpr)

fwrite(hgene.h.bedgraph, quote=FALSE, "/Users/ittaieres/Desktop/Insulator_Experiment/hgene.h.bedgraph", sep="\t", row.names=F, col.names = F)
fwrite(hgene.c.bedgraph, quote=FALSE, "/Users/ittaieres/Desktop/Insulator_Experiment/hgene.c.bedgraph", sep="\t", row.names=F, col.names = F)
fwrite(cgene.c.bedgraph, quote=FALSE, "/Users/ittaieres/Desktop/Insulator_Experiment/cgene.c.bedgraph", sep="\t", row.names=F, col.names = F)
fwrite(cgene.h.bedgraph, quote=FALSE, "/Users/ittaieres/Desktop/Insulator_Experiment/cgene.h.bedgraph", sep="\t", row.names=F, col.names = F)

Permutation Visualizations

Here, I visualize the difference in classes of DE hits changing (either gaining, losing, or maintaining DE status) after “regressing out” the effect of Hi-C from expression. I show distributions of these percentages across 10000 permutations of the data, as compared to the observed percentages.

##Visualization of the permutations!
perm.vis <- function(categories.df.file, df, metadata, hictype, DE=FALSE){
  if(DE==TRUE){expected1 <- readRDS(paste("data/old_mediation_permutations/perm_results/DE/batch1/", categories.df.file, sep=""))
  expected2 <-  readRDS(paste("data/old_mediation_permutations/perm_results/DE/batch2/", categories.df.file, sep=""))
  observed <- lmcorrect(weighted.data, df[which(df$adj.P.Val<=0.05), c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], df[which(df$adj.P.Val<=0.05), c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], metadata)
  }
  else{expected1 <- readRDS(paste("data/old_mediation_permutations/perm_results/batch1/", categories.df.file, sep=""))
  expected2 <- readRDS(paste("data/old_mediation_permutations/perm_results/batch2/", categories.df.file, sep=""))
  observed <- lmcorrect(weighted.data, df[,c("A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651")], df[,c("A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC", "genes")], metadata)
  }
  expected <- c(expected1[1:5000], expected2[1:5000])
  expected[[10001]] <- rbind(expected1[[5001]], expected2[[5001]])
  expected[[10001]] <- ((expected[[10001]])/sum(expected[[10001]][1,]))*100
  for(i in 1:(length(expected)-1)){
  expected[[i]]$type <- i
  expected[[i]]$data <- "expected"
  }
  observed$categories <- (observed$categories/sum(observed$categories[1,]))*100
  observed$stats$type <- 10001
  observed$stats$data <- "observed"
  expected[[10001]]$data <- "permutations"
  expected[[10001]][10001,] <- c(observed$categories, "observation")
  deneitherbox <- ggplot(data=expected[[10001]], aes(x="", y=DEneither)) + geom_boxplot(aes(color="Expected"), show.legend=FALSE) + geom_point(aes(y=observed$categories$DEneither, color="Observed"), size=3) + ggtitle("Percent of genes with no evidence for DE regardless") + ylab("% genes not DE in either") + xlab(paste("10000 Permutations of Hi-C data ", hictype, sep="")) + scale_color_manual(values=c("blue", "red"), guide=FALSE) +guides(color=guide_legend("Data", override.aes = list(shape=c(16, 16))))
  debeforebox <- ggplot(data=expected[[10001]], aes(x="", y=DEbefore)) + geom_boxplot(aes(color="Expected"), show.legend=FALSE) + geom_point(aes(y=observed$categories$DEbefore, color="Observed"), size=3) + ggtitle("Percent of genes with reduced evidence for DE after Hi-C correction") + ylab("% genes DE before, but not after, Hi-C correction") + xlab(paste("10000 Permutations of Hi-C data ", hictype, sep="")) + scale_color_manual(values=c("blue", "red"), guide=FALSE) +guides(color=guide_legend("Data", override.aes = list(shape=c(16, 16))))
  deafterbox <- ggplot(data=expected[[10001]], aes(x="", y=DEafter)) + geom_boxplot(aes(color="Expected"), show.legend=FALSE) + geom_point(aes(y=observed$categories$DEafter, color="Observed"), size=3) + ggtitle("Percent of genes with increased evidence for DE after Hi-C correction") + ylab("% genes DE after, but not before, Hi-C correction") + xlab(paste("10000 Permutations of Hi-C data ", hictype, sep="")) + scale_color_manual(values=c("blue", "red"), guide=FALSE) +guides(color=guide_legend("Data", override.aes = list(shape=c(16, 16))))
  debothbox <- ggplot(data=expected[[10001]], aes(x="", y=DEboth)) + geom_boxplot(aes(color="Expected"), show.legend=FALSE) + geom_point(aes(y=observed$categories$DEboth, color="Observed"), size=3) + ggtitle("Percent of genes with evidence for DE regardless") + ylab("% genes DE in both") + xlab(paste("10000 Permutations of Hi-C data ", hictype, sep="")) + scale_color_manual(values=c("blue", "red"), guide=FALSE) +guides(color=guide_legend("Data", override.aes = list(shape=c(16, 16))))
  print(deneitherbox)
  print(debeforebox)
  print(deafterbox)
  print(debothbox)
}

perm.vis("permout_h_minFDR", hmin, meta.data, "(min FDR contact, Humans)")

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perm.vis("permout_h_maxB", hmaxB, meta.data,  "(max beta contact, Humans)")

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perm.vis("permout_h_US", hUS, meta.data, "(upstream contact, Humans)")

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perm.vis("permout_c_minFDR", cmin, meta.data, "(min FDR contact, Chimps)")

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perm.vis("permout_c_maxB", cmaxB, meta.data, "(max beta contact, Chimps)")

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perm.vis("permout_c_US", cUS, meta.data, "(upstream contact, Chimps)")

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perm.vis("permout_h_minFDR_DE", hminDE, meta.data, "(min FDR contact, Humans)", DE=TRUE)

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perm.vis("permout_h_maxB_DE", hmaxBDE, meta.data,  "(max beta contact, Humans)", DE=TRUE)

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perm.vis("permout_h_US_DE", hUSDE, meta.data, "(upstream contact, Humans)", DE=TRUE)

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perm.vis("permout_c_minFDR_DE", cminDE, meta.data, "(min FDR contact, Chimps)", DE=TRUE)

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perm.vis("permout_c_maxB_DE", cmaxBDE, meta.data, "(max beta contact, Chimps)", DE=TRUE)

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perm.vis("permout_c_US_DE", cUSDE, meta.data, "(upstream contact, Chimps)", DE=TRUE)

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The permutations reveal that the observed data does appear pretty significant: it falls well outside the range of the distributions in each of the categories. The most important is showing that many more genes lose their DE status after regressing out Hi-C data in the observed case as compared to the permutations.

Now, get the appropriate data and actually run the mediation analysis

source("code/mediation_test.R") #Obtain necessary functions
# data already filtered
# expr: log2RPKM
# hic: interaction frequency for each individual per gene
expr <- select(hmin, "A-21792", "B-28126", "C-3649", "D-40300", "E-28815", "F-28834", "G-3624", "H-3651", genes, adj.P.Val) #log2RPKM expression of genes
hic <- select(hmin,"A_21792_HIC", "B_28126_HIC", "C_3649_HIC", "D_40300_HIC", "E_28815_HIC", "F_28834_HIC", "G_3624_HIC", "H_3651_HIC") #Interaction frequency for each individual gene
is_de <- which(expr$adj.P.Val < .05)
isnot_de <- which(expr$adj.P.Val >= .05)
gvec <- expr$genes
expr <- expr[,1:8]

# metadata label
species <- factor(c("H","H","C","C","H","H","C","C"))
sex <- factor(c("F","M" ,"M","F","M", "F","M","F"))

metadata <- data.frame(sample=names(expr)[1:8],
                       species=species, 
                       sex=sex)

###Compute indirect effects. 

fit_de <- test_mediation(exprs = expr[is_de,], 
                         fixed_covariates = list(species=metadata$species,
                                                 sex=metadata$sex),
                         varying_covariate = hic[is_de,])

fit_node <- test_mediation(exprs = expr[isnot_de,], 
                           fixed_covariates = list(species=metadata$species,
                                                   sex=metadata$sex),
                           varying_covariate = hic[isnot_de,])

#Save for running monte carlo on the cluster:
save(fit_de, fit_node, is_de, isnot_de, expr, hic, metadata, gvec, file = "output/homer_mediation.rda")

###Monte Carlo simulation to assess significance; obtaining the Monte Carlo distributions is done on a high-performance computing cluster in order to be able to assess many iterations of random sampling of the data. See the chunk below this one for details on how to obtain the Monte Carlo distributions loaded in here:
mc_de <- readRDS(file = "output/mc_de_homer.rds")
mc_node <- readRDS(file = "output/mc_node_homer.rds")


##In DE genes
ngenes <- ncol(mc_de)
ab <- fit_de$alpha*fit_de$beta
out <- sapply(1:ngenes, function(g) {
  x <- unlist(mc_de[,g])
  q <- quantile(x, prob = c(.025, .975))
#  q <- quantile(x, prob = c(.005, .995))
  ifelse(0 > q[1] & 0 < q[2], F, T)
})
table(out) #Table of TRUE/FALSE for DE genes assessing if the indirect effect (alpha * beta) is non-zero/does not fall within the 95% confidence interval of Monte Carlo simulation.
out
FALSE  TRUE 
 1287   114 
114/(114+1287) #8% of DE genes show significant non-zero mediating effect.
[1] 0.08137045
#Visualize, Fig S16:
DEdat <- data.frame(bf=fit_de$tau, af=fit_de$tau_prime, significance=out)
DEdat$color <- ifelse(DEdat$significance==TRUE, "red", "black")
plot(x=DEdat$bf, y=DEdat$af, ylab="Effect Size After Controlling for Contact", xlab="Effect Size Before Controlling for Contact", main="Effect of Contact on Expression Divergence in DE genes", col=alpha(DEdat$color, 0.6), pch=16, cex=0.6, xlim=c(-10, 10), ylim=c(-10,10))
legend("topleft", legend=c("95% CI Significant (n=114)", "95% CI Non significant (n=1287)"), col=c("red", "black"), pch=16:16, cex=0.8)
abline(0, 1)
abline(h=0)
abline(v=0)

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##In non-DE genes
ngenes <- ncol(mc_node)
ab <- fit_node$alpha*fit_node$beta
out <- sapply(1:ngenes, function(g) {
  x <- unlist(mc_node[,g])
  q <- quantile(x, prob = c(.025, .975))
#  q <- quantile(x, prob = c(.005, .995))
  ifelse(0 > q[1] & 0 < q[2], F, T)
})
table(out) #Similar table to as above.
out
FALSE  TRUE 
 6048   315 
315/(315+6048) #5% of non-DE genes show significant non-zero mediating effect.
[1] 0.04950495
#Visualization for non DE genes:
noDEdat <- data.frame(bf=fit_node$tau, af=fit_node$tau_prime, significance=out)
noDEdat$color <- ifelse(noDEdat$significance==TRUE, "red", "black")
plot(x=noDEdat$bf, y=noDEdat$af, ylab="Effect Size After Controlling for Contact", xlab="Effect Size Before Controlling for Contact", main="Effect of Contact on Expression Divergence in non-DE genes", col=alpha(noDEdat$color, 0.6), pch=16, cex=0.6, xlim=c(-10, 10), ylim=c(-10,10), adj=0.6)
legend("topleft", legend=c("95% CI Significant (n=315)", "95% CI Non significant (n=6048)"), col=c("red", "black"), pch=16:16, cex=0.8)
abline(0, 1)
abline(h=0)
abline(v=0)

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Monte Carlo Specifics; the script used on a computing cluster to obtain Monte Carlo simulations for significance testing

Mediation test intuition and reasoning

The motivation of the current anaysis is to estimate the contribution of contact frequency to phenotype differences (e.g., tissue, species, etc.) in gene expression. In terms of linear models, the hypothesis is that the relationship between independent variable phenotypes and dependent variable gene expression is partially due to the mediating effect of contact frequency. We assess the mediating effect of contact frequency in the association between phenotypes and expression under the following framework.

Consider a hypothetical example. Say we know A causes B, and this relationship may be due to C which is highly correlated with A and and B. The hypothesis is that the relationship between A and B can be explained by the mechansim of A -> C -> B. To quantify the mediating effect of C on the relationship of A and B, we estimate the total effect of A on B and the direct effect of A on B after controlling for C. Total effect of A on B equals the direct effect of A on B after controlling for C and the indirect effect of A on B through C. When the indirect effect is large, we say that C plays a significant role in mediating the relationship between A and B. Applying to the current problem, we hypothesize that the total effect of phenotype on expression equals the direct effect of phenotype on expression after controlling for contact frequency and the indirect effect of phenotype on expression through contact frequency

For each gene, we fit three linear models as follows:

  1. \(Y_g = \gamma_1 + \tau X^P + \epsilon_1 \tag{Eq. 1}\)

  2. \(X^M_g = \gamma_2 + \alpha X^P + \epsilon_2 \tag{Eq. 2}\)

  3. \(Y_g = \gamma_3 + \tau^{\prime} X^P + \beta X^M_g + \epsilon_3 \tag{Eq. 3}\)

\(~\)

Notations:

\(Y_g\): length-\(N\) gene expression vector for gene \(g\).

\(X^M_g\): length-\(N\) vector for chromatin contact measurements corresponding to samples at gene \(g\).

\(X^P\): length-\(N\) vector for sample phenotype labels (species).

\(\tau\): estimated total effect of phenotype (species) \(X^P\) on expression \(Y_g\).

\(\tau^{\prime}\): estimated effect of phenotype (species) \(X^P\) on expression \(Y_g\) after controlling for contact, \(X^M_g\), or the direct effect of phenotype (species) on expression.

\(\alpha\): estimated effect of phenotype (species) \(X^P\) on the chromatin contacts \(X^M_g\).

\(\beta\): estimated effect of chromatin contacts \(X^M_g\) on expression \(Y_g\) after controlling for phenotype (species) differences.

\(\gamma_1, \gamma_2, \gamma_3\): intercepts

\(\epsilon_1, \epsilon_2, \epsilon_3\): error terms in each model. Each assumed to be iid and follows normal distributions with mean 0 and variance \(\sigma^2_1, \sigma^2_2, \sigma^2_3\).

\(~\)

For statistical inference, we use bootstrapping to test for statistical significance of the indirect effect (Preacher and Hayes, 2008). In contrast to the popular [Sobel’s test][sobel], boostrapping doesn’t require normality assumption and independence of mediating and independent variables.

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891.

LogFC DE vs LogFC DC Analysis

#First, do it on all genes.
mydf <- select(gene.hic.filt, adj.P.Val, logFC, min_FDR_B.H)
#+ logFC in DE is higher expression in humans; + logFC in DC is stronger contact in humans
mydf$color <- ifelse(mydf$adj.P.Val<=0.05, "red", "black")
ggplot(mydf, aes(x=logFC, y=min_FDR_B.H)) + geom_point() + xlab("Log FC Expression") + ylab("Log FC Contact Frequency") + ggtitle("LogFC Expression vs. LogFC Contact for All Genes")
Warning: Removed 410 rows containing missing values (geom_point).

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#plot(x=mydf$logFC, y=mydf$min_FDR_B.H, ylab="LogFC DC", xlab="LogFC DE", main="Log Fold Changes, Expression vs. Contact Frequency",  col=mydf$color, pch=16, cex=0.6)
#legend("topleft", legend=c("DE gene", "Non-DE gene"), col=c("red", "black"), pch=16:16, cex=0.8)

mydf <- filter(mydf, adj.P.Val<=0.05)
mydf$color <- ifelse(mydf$logFC>0, "red", "blue")
#colnames(mydf)[4] <- "Species with higher expression"
ggplot(mydf, aes(x=logFC, y=min_FDR_B.H, color=color)) + geom_point() + xlab("Log FC Expression") + ylab("Log FC Contact Frequency") + ggtitle("LogFC Expression vs. LogFC Contact for DE Genes") + scale_color_discrete(name="Higher Expression", labels=c("Chimp", "Human"))
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#plot(y=mydf$logFC, x=mydf$min_FDR_B.H, ylab="LogFC DE", xlab="LogFC DC", main="Log Fold Changes, Expression vs. Contact Frequency",  col=mydf$color)
#legend("topleft", legend=c("Significant higher expression in humans", "Significant higher expression in chimps"), col=c("red", "blue"), pch=16:16, cex=0.8)

#Alternative method:
#Simple plotting of logFC vs logFC. A positive logFC from the expression data indicates higher expression in humans.
#First, perform for entire set of genes, on non-DE and DE genes separately.
mydat <- select(gene.hic.filt, logFC, min_FDR_B.H, adj.P.Val, AveExpr)
ggplot(mydat) + geom_point(aes(x=logFC, y=min_FDR_B.H, color=adj.P.Val))
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ggplot(filter(mydat, adj.P.Val<=0.05)) + geom_point(aes(x=logFC, y=min_FDR_B.H)) + xlab("LogFC, Expression") + ylab("LogFC, Contact") + ggtitle("LogFC Expression vs. LogFC Contact for DE Genes")
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ggplot(filter(mydat, adj.P.Val>0.05)) + geom_point(aes(x=logFC, y=min_FDR_B.H)) + xlab("LogFC, Expression") + ylab("LogFC, Contact") + ggtitle("LogFC Expression vs. LogFC Contact for non-DE Genes")
Warning: Removed 329 rows containing missing values (geom_point).

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#Now, take a look at what happens if I stratify things by which species it's more highly expressed in, and its DE status, and calculate R-squareds. Should do this with actual mean expression values per species
human.high.DE <- filter(mydat, logFC>0, adj.P.Val<=0.05)
human.high.nonDE <- filter(mydat, logFC>0, adj.P.Val>0.05)
chimp.high.DE <- filter(mydat, logFC<0, adj.P.Val<=0.05)
chimp.high.nonDE <- filter(mydat, logFC<0, adj.P.Val>0.05)
summary(lm(human.high.nonDE$logFC~human.high.nonDE$min_FDR_B.H))$adj.r.squared
[1] -0.0002948177
summary(lm(human.high.DE$logFC~human.high.DE$min_FDR_B.H))$adj.r.squared
[1] -0.001316947
summary(lm(chimp.high.nonDE$logFC~chimp.high.nonDE$min_FDR_B.H))$adj.r.squared
[1] 0.0004172514
summary(lm(chimp.high.DE$logFC~chimp.high.DE$min_FDR_B.H))$adj.r.squared
[1] 0.0008310352

sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] grid      compiler  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] VennDiagram_1.6.20  futile.logger_1.4.3 glmnet_2.0-16      
 [4] foreach_1.4.7       Matrix_1.2-17       medinome_0.0.1     
 [7] vashr_0.99.1        qvalue_2.10.0       SQUAREM_2017.10-1  
[10] ashr_2.2-32         forcats_0.4.0       purrr_0.3.2        
[13] readr_1.3.1         tibble_2.1.3        tidyverse_1.2.1    
[16] edgeR_3.20.9        RColorBrewer_1.1-2  heatmaply_0.16.0   
[19] viridis_0.5.1       viridisLite_0.3.0   stringr_1.4.0      
[22] gplots_3.0.1.1      Hmisc_4.2-0         Formula_1.2-3      
[25] survival_2.44-1.1   lattice_0.20-38     dplyr_0.8.3        
[28] plotly_4.9.0        cowplot_0.9.4       ggplot2_3.2.1      
[31] reshape2_1.4.3      data.table_1.12.0   tidyr_1.0.0        
[34] plyr_1.8.4          limma_3.34.9       

loaded via a namespace (and not attached):
 [1] colorspace_1.4-1     rprojroot_1.3-2      htmlTable_1.13.2    
 [4] base64enc_0.1-3      fs_1.3.1             rstudioapi_0.10     
 [7] lubridate_1.7.4      xml2_1.2.2           codetools_0.2-16    
[10] splines_3.4.0        pscl_1.5.2           doParallel_1.0.15   
[13] knitr_1.22           zeallot_0.1.0        jsonlite_1.6        
[16] workflowr_1.4.0      broom_0.5.2          cluster_2.0.7-1     
[19] httr_1.4.1           backports_1.1.4      assertthat_0.2.1    
[22] lazyeval_0.2.2       cli_1.1.0            formatR_1.7         
[25] acepack_1.4.1        htmltools_0.3.6      tools_3.4.0         
[28] gtable_0.3.0         glue_1.3.1           Rcpp_1.0.1          
[31] cellranger_1.1.0     vctrs_0.2.0          gdata_2.18.0        
[34] nlme_3.1-137         iterators_1.0.12     xfun_0.5            
[37] rvest_0.3.4          lifecycle_0.1.0      gtools_3.8.1        
[40] dendextend_1.12.0    MASS_7.3-51.4        scales_1.0.0        
[43] TSP_1.1-7            hms_0.5.1            parallel_3.4.0      
[46] lambda.r_1.2.4       yaml_2.2.0           gridExtra_2.3       
[49] rpart_4.1-15         latticeExtra_0.6-28  stringi_1.4.3       
[52] highr_0.8            gclus_1.3.2          checkmate_1.9.4     
[55] seriation_1.2-3      caTools_1.17.1.2     truncnorm_1.0-8     
[58] rlang_0.4.0          pkgconfig_2.0.3      bitops_1.0-6        
[61] evaluate_0.13        labeling_0.3         htmlwidgets_1.3     
[64] tidyselect_0.2.5     magrittr_1.5         R6_2.4.0            
[67] generics_0.0.2       pillar_1.4.2         haven_2.1.1         
[70] whisker_0.4          foreign_0.8-72       withr_2.1.2         
[73] mixsqp_0.1-97        nnet_7.3-12          modelr_0.1.5        
[76] crayon_1.3.4         futile.options_1.0.1 KernSmooth_2.23-15  
[79] rmarkdown_1.12       locfit_1.5-9.1       readxl_1.3.1        
[82] git2r_0.26.1         digest_0.6.18        webshot_0.5.1       
[85] munsell_0.5.0        registry_0.5-1