# HG changeset patch # User fubar # Date 1421723639 18000 # Node ID c1b3da0fde4a2ccc4437cdb6b9d115095549e097 # Parent a72211e03b3883725237d6cfb791e21fb3d188d6 Uploaded diff -r a72211e03b38 -r c1b3da0fde4a hairpinTool.R --- a/hairpinTool.R Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1069 +0,0 @@ -#!/usr/bin/env Rscript -# ARGS: 1.inputType -String specifying format of input (fastq or table) -# IF inputType is "fastq" or "pairedFastq: -# 2*.fastqPath -One or more strings specifying path to fastq files -# 2.annoPath -String specifying path to hairpin annotation table -# 3.samplePath -String specifying path to sample annotation table -# 4.barStart -Integer specifying starting position of barcode -# 5.barEnd -Integer specifying ending position of barcode -# ### -# IF inputType is "pairedFastq": -# 6.barStartRev -Integer specifying starting position of barcode -# on reverse end -# 7.barEndRev -Integer specifying ending position of barcode -# on reverse end -# ### -# 8.hpStart -Integer specifying startins position of hairpin -# unique region -# 9.hpEnd -Integer specifying ending position of hairpin -# unique region -# IF inputType is "counts": -# 2.countPath -String specifying path to count table -# 3.annoPath -String specifying path to hairpin annotation table -# 4.samplePath -String specifying path to sample annotation table -# ### -# 10.secFactName -String specifying name of secondary factor -# 11.cpmReq -Float specifying cpm requirement -# 12.sampleReq -Integer specifying cpm requirement -# 13.readReq -Integer specifying read requirement -# 14.fdrThresh -Float specifying the FDR requirement -# 15.lfcThresh -Float specifying the log-fold-change requirement -# 16.workMode -String specifying exact test or GLM usage -# 17.htmlPath -String specifying path to HTML file -# 18.folderPath -String specifying path to folder for output -# IF workMode is "classic" (exact test) -# 19.pairData[2] -String specifying first group for exact test -# 20.pairData[1] -String specifying second group for exact test -# ### -# IF workMode is "glm" -# 19.contrastData -String specifying contrasts to be made -# 20.roastOpt -String specifying usage of gene-wise tests -# 21.hairpinReq -String specifying hairpin requirement for gene- -# wise test -# 22.selectOpt -String specifying type of selection for barcode -# plots -# 23.selectVals -String specifying members selected for barcode -# plots -# ### -# -# OUT: Bar Plot of Counts Per Index -# Bar Plot of Counts Per Hairpin -# MDS Plot -# BCV Plot -# Smear Plot -# Barcode Plots (If Genewise testing was selected) -# Top Expression Table -# Feature Counts Table -# HTML file linking to the ouputs -# -# Author: Shian Su - registertonysu@gmail.com - Jan 2014 - -# Record starting time -timeStart <- as.character(Sys.time()) -options(bitmapType='cairo') -# needed to prevent missing x11 errors for png() -# Loading and checking required packages -library(methods, quietly=TRUE, warn.conflicts=FALSE) -library(statmod, quietly=TRUE, warn.conflicts=FALSE) -library(splines, quietly=TRUE, warn.conflicts=FALSE) -library(edgeR, quietly=TRUE, warn.conflicts=FALSE) -library(limma, quietly=TRUE, warn.conflicts=FALSE) - -if (packageVersion("edgeR") < "3.7.17") { - stop("Please update 'edgeR' to version >= 3.7.17 to run this tool") -} - -if (packageVersion("limma")<"3.21.16") { - message("Update 'limma' to version >= 3.21.16 to see updated barcode graphs") -} - -################################################################################ -### Function declarations -################################################################################ - -# Function to load libaries without messages -silentLibrary <- function(...) { - list <- c(...) - for (package in list){ - suppressPackageStartupMessages(library(package, character.only=TRUE)) - } -} - -# Function to sanitise contrast equations so there are no whitespaces -# surrounding the arithmetic operators, leading or trailing whitespace -sanitiseEquation <- function(equation) { - equation <- gsub(" *[+] *", "+", equation) - equation <- gsub(" *[-] *", "-", equation) - equation <- gsub(" *[/] *", "/", equation) - equation <- gsub(" *[*] *", "*", equation) - equation <- gsub("^\\s+|\\s+$", "", equation) - return(equation) -} - -# Function to sanitise group information -sanitiseGroups <- function(string) { - string <- gsub(" *[,] *", ",", string) - string <- gsub("^\\s+|\\s+$", "", string) - return(string) -} - -# Function to change periods to whitespace in a string -unmake.names <- function(string) { - string <- gsub(".", " ", string, fixed=TRUE) - return(string) -} - -# Function has string input and generates an output path string -makeOut <- function(filename) { - return(paste0(folderPath, "/", filename)) -} - -# Function has string input and generates both a pdf and png output strings -imgOut <- function(filename) { - assign(paste0(filename, "Png"), makeOut(paste0(filename,".png")), - envir=.GlobalEnv) - assign(paste0(filename, "Pdf"), makeOut(paste0(filename,".pdf")), - envir=.GlobalEnv) -} - -# Create cat function default path set, default seperator empty and appending -# true by default (Ripped straight from the cat function with altered argument -# defaults) -cata <- function(..., file=htmlPath, sep="", fill=FALSE, labels=NULL, - append=TRUE) { - if (is.character(file)) - if (file == "") - file <- stdout() - else if (substring(file, 1L, 1L) == "|") { - file <- pipe(substring(file, 2L), "w") - on.exit(close(file)) - } - else { - file <- file(file, ifelse(append, "a", "w")) - on.exit(close(file)) - } - .Internal(cat(list(...), file, sep, fill, labels, append)) -} - -# Function to write code for html head and title -HtmlHead <- function(title) { - cata("\n") - cata("", title, "\n") - cata("\n") -} - -# Function to write code for html links -HtmlLink <- function(address, label=address) { - cata("", label, "
\n") -} - -# Function to write code for html images -HtmlImage <- function(source, label=source, height=600, width=600) { - cata("\"",\n") -} - -# Function to write code for html list items -ListItem <- function(...) { - cata("
  • ", ..., "
    • \n") -} - -TableItem <- function(...) { - cata("", ..., "\n") -} - -TableHeadItem <- function(...) { - cata("", ..., "\n") -} -################################################################################ -### Input Processing -################################################################################ - -# Grabbing arguments from command line -argv <- commandArgs(T) - -inputType <- as.character(argv[1]) -if (inputType == "fastq") { - - fastqPath <- as.character(gsub("fastq::", "", argv[grepl("fastq::", argv)], - fixed=TRUE)) - - # Remove fastq paths - argv <- argv[!grepl("fastq::", argv, fixed=TRUE)] - - fastqPathRev <- NULL - annoPath <- as.character(argv[2]) - samplePath <- as.character(argv[3]) - barStart <- as.numeric(argv[4]) - barEnd <- as.numeric(argv[5]) - barStartRev <- NULL - barStartRev <- NULL - hpStart <- as.numeric(argv[8]) - hpEnd <- as.numeric(argv[9]) -} else if (inputType=="pairedFastq") { - - fastqPath <- as.character(gsub("fastq::", "", argv[grepl("fastq::", argv)], - fixed=TRUE)) - - fastqPathRev <- as.character(gsub("fastqRev::", "", - argv[grepl("fastqRev::", argv)], fixed=TRUE)) - - # Remove fastq paths - argv <- argv[!grepl("fastq::", argv, fixed=TRUE)] - argv <- argv[!grepl("fastqRev::", argv, fixed=TRUE)] - - annoPath <- as.character(argv[2]) - samplePath <- as.character(argv[3]) - barStart <- as.numeric(argv[4]) - barEnd <- as.numeric(argv[5]) - barStartRev <- as.numeric(argv[6]) - barEndRev <- as.numeric(argv[7]) - hpStart <- as.numeric(argv[8]) - hpEnd <- as.numeric(argv[9]) -} else if (inputType == "counts") { - countPath <- as.character(argv[2]) - annoPath <- as.character(argv[3]) - samplePath <- as.character(argv[4]) -} - -secFactName <- as.character(argv[10]) -cpmReq <- as.numeric(argv[11]) -sampleReq <- as.numeric(argv[12]) -readReq <- as.numeric(argv[13]) -fdrThresh <- as.numeric(argv[14]) -lfcThresh <- as.numeric(argv[15]) -selectDirection <- as.character(argv[16]) -workMode <- as.character(argv[17]) -htmlPath <- as.character(argv[18]) -folderPath <- as.character(argv[19]) - -if (workMode == "classic") { - pairData <- character() - pairData[2] <- as.character(argv[20]) - pairData[1] <- as.character(argv[21]) -} else if (workMode == "glm") { - contrastData <- as.character(argv[20]) - roastOpt <- as.character(argv[21]) - hairpinReq <- as.numeric(argv[22]) - selectOpt <- as.character(argv[23]) - selectVals <- as.character(argv[24]) -} - -# Read in inputs - -samples <- read.table(samplePath, header=TRUE, sep="\t") - -anno <- read.table(annoPath, header=TRUE, sep="\t") - -if (inputType == "counts") { - counts <- read.table(countPath, header=TRUE, sep="\t") -} - -###################### Check inputs for correctness ############################ -samples$ID <- make.names(samples$ID) - -if ( !any(grepl("group", names(samples))) ) { - stop("'group' column not specified in sample annotation file") -} # Check if grouping variable has been specified - -if (secFactName != "none") { - if ( !any(grepl(secFactName, names(samples))) ) { - tempStr <- paste0("Second factor specified as \"", secFactName, "\" but ", - "no such column name found in sample annotation file") - stop(tempStr) - } # Check if specified secondary factor is present -} - - -if ( any(table(samples$ID) > 1) ){ - tab <- table(samples$ID) - offenders <- paste(names(tab[tab > 1]), collapse=", ") - offenders <- unmake.names(offenders) - stop("'ID' column of sample annotation must have unique values, values ", - offenders, " are repeated") -} # Check that IDs in sample annotation are unique - -if (inputType == "fastq" || inputType == "pairedFastq") { - - if ( any(table(anno$ID) > 1) ){ - tab <- table(anno$ID) - offenders <- paste(names(tab[tab>1]), collapse=", ") - stop("'ID' column of hairpin annotation must have unique values, values ", - offenders, " are repeated") - } # Check that IDs in hairpin annotation are unique - -} else if (inputType == "counts") { - # The first element of the colnames will be 'ID' and should not match - idFromSample <- samples$ID - idFromTable <- colnames(counts)[-1] - if (any(is.na(match(idFromTable, idFromSample)))) { - stop("not all samples have groups specified") - } # Check that a group has be specifed for each sample - - if ( any(table(counts$ID) > 1) ){ - tab <- table(counts$ID) - offenders <- paste(names(tab[tab>1]), collapse=", ") - stop("'ID' column of count table must have unique values, values ", - offenders, " are repeated") - } # Check that IDs in count table are unique -} -if (workMode == "glm") { - if (roastOpt == "yes") { - if (is.na(match("Gene", colnames(anno)))) { - tempStr <- paste("Gene-wise tests selected but'Gene' column not", - "specified in hairpin annotation file") - stop(tempStr) - } - } -} - -if (secFactName != "none") { - if (workMode != "glm") { - tempStr <- paste("only glm analysis type possible when secondary factor", - "used, please change appropriate option.") - } -} - -################################################################################ - -# Process arguments -if (workMode == "glm") { - if (roastOpt == "yes") { - wantRoast <- TRUE - } else { - wantRoast <- FALSE - } -} - -# Split up contrasts seperated by comma into a vector and replace spaces with -# periods -if (exists("contrastData")) { - contrastData <- unlist(strsplit(contrastData, split=",")) - contrastData <- sanitiseEquation(contrastData) - contrastData <- gsub(" ", ".", contrastData, fixed=TRUE) -} - -# Replace spaces with periods in pair data -if (exists("pairData")) { - pairData <- make.names(pairData) -} - -# Generate output folder and paths -dir.create(folderPath, showWarnings=FALSE) - -# Generate links for outputs -imgOut("barHairpin") -imgOut("barIndex") -imgOut("mds") -imgOut("bcv") -if (workMode == "classic") { - smearPng <- makeOut(paste0("smear(", pairData[2], "-", pairData[1],").png")) - smearPdf <- makeOut(paste0("smear(", pairData[2], "-", pairData[1],").pdf")) - topOut <- makeOut(paste0("toptag(", pairData[2], "-", pairData[1],").tsv")) -} else if (workMode == "glm") { - smearPng <- character() - smearPdf <- character() - topOut <- character() - roastOut <- character() - barcodePng <- character() - barcodePdf <- character() - for (i in 1:length(contrastData)) { - smearPng[i] <- makeOut(paste0("smear(", contrastData[i], ").png")) - smearPdf[i] <- makeOut(paste0("smear(", contrastData[i], ").pdf")) - topOut[i] <- makeOut(paste0("toptag(", contrastData[i], ").tsv")) - roastOut[i] <- makeOut(paste0("gene_level(", contrastData[i], ").tsv")) - barcodePng[i] <- makeOut(paste0("barcode(", contrastData[i], ").png")) - barcodePdf[i] <- makeOut(paste0("barcode(", contrastData[i], ").pdf")) - } -} -countsOut <- makeOut("counts.tsv") -sessionOut <- makeOut("session_info.txt") - -# Initialise data for html links and images, table with the link label and -# link address -linkData <- data.frame(Label=character(), Link=character(), - stringsAsFactors=FALSE) -imageData <- data.frame(Label=character(), Link=character(), - stringsAsFactors=FALSE) - -# Initialise vectors for storage of up/down/neutral regulated counts -upCount <- numeric() -downCount <- numeric() -flatCount <- numeric() - -################################################################################ -### Data Processing -################################################################################ - -# Transform gene selection from string into index values for mroast -if (workMode == "glm") { - if (selectOpt == "rank") { - selectVals <- gsub(" ", "", selectVals, fixed=TRUE) - selectVals <- unlist(strsplit(selectVals, ",")) - - for (i in 1:length(selectVals)) { - if (grepl(":", selectVals[i], fixed=TRUE)) { - temp <- unlist(strsplit(selectVals[i], ":")) - selectVals <- selectVals[-i] - a <- as.numeric(temp[1]) - b <- as.numeric(temp[2]) - selectVals <- c(selectVals, a:b) - } - } - selectVals <- as.numeric(unique(selectVals)) - } else { - selectVals <- gsub(" ", "", selectVals, fixed=TRUE) - selectVals <- unlist(strsplit(selectVals, ",")) - } -} - -if (inputType == "fastq" || inputType == "pairedFastq") { - # Use EdgeR hairpin process and capture outputs - - hpReadout <- capture.output( - data <- processAmplicons(readfile=fastqPath, readfile2=fastqPathRev, - barcodefile=samplePath, - hairpinfile=annoPath, - barcodeStart=barStart, barcodeEnd=barEnd, - barcodeStartRev=barStartRev, - barcodeEndRev=barEndRev, - hairpinStart=hpStart, hairpinEnd=hpEnd, - verbose=TRUE) - ) - - # Remove function output entries that show processing data or is empty - hpReadout <- hpReadout[hpReadout!=""] - hpReadout <- hpReadout[!grepl("Processing", hpReadout)] - hpReadout <- hpReadout[!grepl("in file", hpReadout)] - hpReadout <- gsub(" -- ", "", hpReadout, fixed=TRUE) - - # Make the names of groups syntactically valid (replace spaces with periods) - data$samples$group <- make.names(data$samples$group) - if (secFactName != "none") { - data$samples[[secFactName]] <- make.names(data$samples[[secFactName]]) - } -} else if (inputType == "counts") { - # Process counts information, set ID column to be row names - rownames(counts) <- counts$ID - counts <- counts[ , !(colnames(counts) == "ID")] - countsRows <- nrow(counts) - - # Process group information - sampleNames <- colnames(counts) - matchedIndex <- match(sampleNames, samples$ID) - factors <- samples$group[matchedIndex] - - if (secFactName != "none") { - secFactors <- samples[[secFactName]][matchedIndex] - } - - annoRows <- nrow(anno) - anno <- anno[match(rownames(counts), anno$ID), ] - annoMatched <- sum(!is.na(anno$ID)) - - if (any(is.na(anno$ID))) { - warningStr <- paste("count table contained more hairpins than", - "specified in hairpin annotation file") - warning(warningStr) - } - - # Filter out rows with zero counts - sel <- rowSums(counts)!=0 - counts <- counts[sel, ] - anno <- anno[sel, ] - - # Create DGEList - data <- DGEList(counts=counts, lib.size=colSums(counts), - norm.factors=rep(1,ncol(counts)), genes=anno, group=factors) - - # Make the names of groups syntactically valid (replace spaces with periods) - data$samples$group <- make.names(data$samples$group) -} - -# Filter out any samples with zero counts -if (any(data$samples$lib.size == 0)) { - sampleSel <- data$samples$lib.size != 0 - filteredSamples <- paste(data$samples$ID[!sampleSel], collapse=", ") - data$counts <- data$counts[, sampleSel] - data$samples <- data$samples[sampleSel, ] -} - -# Filter hairpins with low counts -preFilterCount <- nrow(data) -selRow <- rowSums(cpm(data$counts) > cpmReq) >= sampleReq -selCol <- colSums(data$counts) > readReq -data <- data[selRow, selCol] - -# Check if any data survived filtering -if (length(data$counts) == 0) { - stop("no data remains after filtering, consider relaxing filters") -} - -# Count number of filtered tags and samples -postFilterCount <- nrow(data) -filteredCount <- preFilterCount - postFilterCount -sampleFilterCount <- sum(!selCol) - -if (secFactName == "none") { - # Estimate dispersions - data <- estimateDisp(data) - commonBCV <- round(sqrt(data$common.dispersion), 4) -} else { - # Construct design - if (inputType == "counts") { - - sampleNames <- colnames(counts) - matchedIndex <- match(sampleNames, samples$ID) - factors <- factor(make.names(samples$group[matchedIndex])) - - secFactors <- factor(make.names(samples[[secFactName]][matchedIndex])) - - } else if (inputType == "fastq" || inputType == "pairedFastq") { - - factors <- factor(data$sample$group) - secFactors <- factor(data$sample[[secFactName]]) - - } - - design <- model.matrix(~0 + factors + secFactors) - - # Estimate dispersions - data <- estimateDisp(data, design=design) - commonBCV <- round(sqrt(data$common.dispersion), 4) -} - - -################################################################################ -### Output Processing -################################################################################ - -# Plot number of hairpins that could be matched per sample -png(barIndexPng, width=600, height=600) -barplot(height<-colSums(data$counts), las=2, main="Counts per index", - cex.names=1.0, cex.axis=0.8, ylim=c(0, max(height)*1.2)) -imageData[1, ] <- c("Counts per Index", "barIndex.png") -invisible(dev.off()) - -pdf(barIndexPdf) -barplot(height<-colSums(data$counts), las=2, main="Counts per index", - cex.names=1.0, cex.axis=0.8, ylim=c(0, max(height)*1.2)) -linkData[1, ] <- c("Counts per Index Barplot (.pdf)", "barIndex.pdf") -invisible(dev.off()) - -# Plot per hairpin totals across all samples -png(barHairpinPng, width=600, height=600) -if (nrow(data$counts)<50) { - barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin", - cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2)) -} else { - barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin", - cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2), - names.arg=FALSE) -} -imageData <- rbind(imageData, c("Counts per Hairpin", "barHairpin.png")) -invisible(dev.off()) - -pdf(barHairpinPdf) -if (nrow(data$counts)<50) { - barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin", - cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2)) -} else { - barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin", - cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2), - names.arg=FALSE) -} -newEntry <- c("Counts per Hairpin Barplot (.pdf)", "barHairpin.pdf") -linkData <- rbind(linkData, newEntry) -invisible(dev.off()) - -# Make an MDS plot to visualise relationships between replicate samples -png(mdsPng, width=600, height=600) -plotMDS(data, labels=data$samples$group, col=as.numeric(data$samples$group), main="MDS Plot") -imageData <- rbind(imageData, c("MDS Plot", "mds.png")) -invisible(dev.off()) - -pdf(mdsPdf) -plotMDS(data, labels=data$samples$group, col=as.numeric(data$samples$group),main="MDS Plot") -newEntry <- c("MDS Plot (.pdf)", "mds.pdf") -linkData <- rbind(linkData, newEntry) -invisible(dev.off()) - -# BCV Plot -png(bcvPng, width=600, height=600) -plotBCV(data, main="BCV Plot") -imageData <- rbind(imageData, c("BCV Plot", "bcv.png")) -invisible(dev.off()) - -pdf(bcvPdf) -plotBCV(data, main="BCV Plot") -newEntry <- c("BCV Plot (.pdf)", "bcv.pdf") -linkData <- rbind(linkData, newEntry) -invisible(dev.off()) - -if (workMode == "classic") { - # Assess differential representation using classic exact testing methodology - # in edgeR - testData <- exactTest(data, pair=pairData) - - top <- topTags(testData, n=Inf) - - if (selectDirection == "all") { - topIDs <- top$table[(top$table$FDR < fdrThresh) & - (abs(top$table$logFC) > lfcThresh), 1] - } else if (selectDirection == "up") { - topIDs <- top$table[(top$table$FDR < fdrThresh) & - (top$table$logFC > lfcThresh), 1] - } else if (selectDirection == "down") { - topIDs <- top$table[(top$table$FDR < fdrThresh) & - (top$table$logFC < -lfcThresh), 1] -} - - write.table(top, file=topOut, row.names=FALSE, sep="\t") - - linkName <- paste0("Top Tags Table(", pairData[2], "-", pairData[1], - ") (.tsv)") - linkAddr <- paste0("toptag(", pairData[2], "-", pairData[1], ").tsv") - linkData <- rbind(linkData, c(linkName, linkAddr)) - - upCount[1] <- sum(top$table$FDR < fdrThresh & top$table$logFC > lfcThresh) - - downCount[1] <- sum(top$table$FDR < fdrThresh & - top$table$logFC < -lfcThresh) - - flatCount[1] <- sum(top$table$FDR > fdrThresh | - abs(top$table$logFC) < lfcThresh) - - - - # Select hairpins with FDR < 0.05 to highlight on plot - png(smearPng, width=600, height=600) - plotTitle <- gsub(".", " ", - paste0("Smear Plot: ", pairData[2], "-", pairData[1]), - fixed=TRUE) - plotSmear(testData, de.tags=topIDs, - pch=20, cex=1.0, main=plotTitle) - abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2) - imgName <- paste0("Smear Plot(", pairData[2], "-", pairData[1], ")") - imgAddr <- paste0("smear(", pairData[2], "-", pairData[1],").png") - imageData <- rbind(imageData, c(imgName, imgAddr)) - invisible(dev.off()) - - pdf(smearPdf) - plotTitle <- gsub(".", " ", - paste0("Smear Plot: ", pairData[2], "-", pairData[1]), - fixed=TRUE) - plotSmear(testData, de.tags=topIDs, - pch=20, cex=1.0, main=plotTitle) - abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2) - imgName <- paste0("Smear Plot(", pairData[2], "-", pairData[1], ") (.pdf)") - imgAddr <- paste0("smear(", pairData[2], "-", pairData[1], ").pdf") - linkData <- rbind(linkData, c(imgName, imgAddr)) - invisible(dev.off()) - -} else if (workMode == "glm") { - # Generating design information - if (secFactName == "none") { - - factors <- factor(data$sample$group) - design <- model.matrix(~0 + factors) - - colnames(design) <- gsub("factors", "", colnames(design), fixed=TRUE) - - } else { - - factors <- factor(data$sample$group) - - if (inputType == "counts") { - - sampleNames <- colnames(counts) - matchedIndex <- match(sampleNames, samples$ID) - factors <- factor(samples$group[matchedIndex]) - - secFactors <- factor(samples[[secFactName]][matchedIndex]) - - } else if (inputType == "fastq" || inputType == "pairedFastq") { - - secFactors <- factor(data$sample[[secFactName]]) - - } - - design <- model.matrix(~0 + factors + secFactors) - - colnames(design) <- gsub("factors", "", colnames(design), fixed=TRUE) - colnames(design) <- gsub("secFactors", secFactName, colnames(design), - fixed=TRUE) - } - - - # Split up contrasts seperated by comma into a vector - contrastData <- unlist(strsplit(contrastData, split=",")) - - for (i in 1:length(contrastData)) { - # Generate contrasts information - contrasts <- makeContrasts(contrasts=contrastData[i], levels=design) - - # Fit negative bionomial GLM - fit <- glmFit(data, design) - # Carry out Likelihood ratio test - testData <- glmLRT(fit, contrast=contrasts) - - # Select hairpins with FDR < 0.05 to highlight on plot - top <- topTags(testData, n=Inf) - - if (selectDirection == "all") { - topIDs <- top$table[(top$table$FDR < fdrThresh) & - (abs(top$table$logFC) > lfcThresh), 1] - } else if (selectDirection == "up") { - topIDs <- top$table[(top$table$FDR < fdrThresh) & - (top$table$logFC > lfcThresh), 1] - } else if (selectDirection == "down") { - topIDs <- top$table[(top$table$FDR < fdrThresh) & - (top$table$logFC < -lfcThresh), 1] - } - - write.table(top, file=topOut[i], row.names=FALSE, sep="\t") - - linkName <- paste0("Top Tags Table(", contrastData[i], ") (.tsv)") - linkAddr <- paste0("toptag(", contrastData[i], ").tsv") - linkData <- rbind(linkData, c(linkName, linkAddr)) - - # Collect counts for differential representation - upCount[i] <- sum(top$table$FDR < fdrThresh & top$table$logFC > lfcThresh) - downCount[i] <- sum(top$table$FDR < fdrThresh & - top$table$logFC < -lfcThresh) - flatCount[i] <- sum(top$table$FDR > fdrThresh | - abs(top$table$logFC) < lfcThresh) - - # Make a plot of logFC versus logCPM - png(smearPng[i], height=600, width=600) - plotTitle <- paste("Smear Plot:", gsub(".", " ", contrastData[i], - fixed=TRUE)) - plotSmear(testData, de.tags=topIDs, pch=20, cex=0.8, main=plotTitle) - abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2) - - imgName <- paste0("Smear Plot(", contrastData[i], ")") - imgAddr <- paste0("smear(", contrastData[i], ").png") - imageData <- rbind(imageData, c(imgName, imgAddr)) - invisible(dev.off()) - - pdf(smearPdf[i]) - plotTitle <- paste("Smear Plot:", gsub(".", " ", contrastData[i], - fixed=TRUE)) - plotSmear(testData, de.tags=topIDs, pch=20, cex=0.8, main=plotTitle) - abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2) - - linkName <- paste0("Smear Plot(", contrastData[i], ") (.pdf)") - linkAddr <- paste0("smear(", contrastData[i], ").pdf") - linkData <- rbind(linkData, c(linkName, linkAddr)) - invisible(dev.off()) - - genes <- as.character(data$genes$Gene) - unq <- unique(genes) - unq <- unq[!is.na(unq)] - geneList <- list() - for (gene in unq) { - if (length(which(genes == gene)) >= hairpinReq) { - geneList[[gene]] <- which(genes == gene) - } - } - - if (wantRoast) { - # Input preparaton for roast - nrot <- 9999 - set.seed(602214129) - roastData <- mroast(data, index=geneList, design=design, - contrast=contrasts, nrot=nrot) - roastData <- cbind(GeneID=rownames(roastData), roastData) - write.table(roastData, file=roastOut[i], row.names=FALSE, sep="\t") - linkName <- paste0("Gene Level Analysis Table(", contrastData[i], - ") (.tsv)") - linkAddr <- paste0("gene_level(", contrastData[i], ").tsv") - linkData <- rbind(linkData, c(linkName, linkAddr)) - if (selectOpt == "rank") { - selectedGenes <- rownames(roastData)[selectVals] - } else { - selectedGenes <- selectVals - } - - if (packageVersion("limma")<"3.19.19") { - png(barcodePng[i], width=600, height=length(selectedGenes)*150) - } else { - png(barcodePng[i], width=600, height=length(selectedGenes)*300) - } - par(mfrow=c(length(selectedGenes), 1)) - for (gene in selectedGenes) { - barcodeplot(testData$table$logFC, index=geneList[[gene]], - main=paste("Barcode Plot for", gene, "(logFCs)", - gsub(".", " ", contrastData[i])), - labels=c("Positive logFC", "Negative logFC")) - } - imgName <- paste0("Barcode Plot(", contrastData[i], ")") - imgAddr <- paste0("barcode(", contrastData[i], ").png") - imageData <- rbind(imageData, c(imgName, imgAddr)) - dev.off() - if (packageVersion("limma")<"3.19.19") { - pdf(barcodePdf[i], width=8, height=2) - } else { - pdf(barcodePdf[i], width=8, height=4) - } - for (gene in selectedGenes) { - barcodeplot(testData$table$logFC, index=geneList[[gene]], - main=paste("Barcode Plot for", gene, "(logFCs)", - gsub(".", " ", contrastData[i])), - labels=c("Positive logFC", "Negative logFC")) - } - linkName <- paste0("Barcode Plot(", contrastData[i], ") (.pdf)") - linkAddr <- paste0("barcode(", contrastData[i], ").pdf") - linkData <- rbind(linkData, c(linkName, linkAddr)) - dev.off() - } - } -} - -# Generate data frame of the significant differences -sigDiff <- data.frame(Up=upCount, Flat=flatCount, Down=downCount) -if (workMode == "glm") { - - row.names(sigDiff) <- contrastData - -} else if (workMode == "classic") { - - row.names(sigDiff) <- paste0(pairData[2], "-", pairData[1]) - -} - -# Output table of summarised counts -ID <- rownames(data$counts) -outputCounts <- cbind(ID, data$counts) -write.table(outputCounts, file=countsOut, row.names=FALSE, sep="\t", - quote=FALSE) -linkName <- "Counts table (.tsv)" -linkAddr <- "counts.tsv" -linkData <- rbind(linkData, c(linkName, linkAddr)) - -# Record session info -writeLines(capture.output(sessionInfo()), sessionOut) -linkData <- rbind(linkData, c("Session Info", "session_info.txt")) - -# Record ending time and calculate total run time -timeEnd <- as.character(Sys.time()) -timeTaken <- capture.output(round(difftime(timeEnd,timeStart), digits=3)) -timeTaken <- gsub("Time difference of ", "", timeTaken, fixed=TRUE) -################################################################################ -### HTML Generation -################################################################################ -# Clear file -cat("", file=htmlPath) - -cata("\n") -HtmlHead("EdgeR Output") - -cata("\n") -cata("

    EdgeR Analysis Output:

    \n") -cata("

    Input Summary:

    \n") -if (inputType == "fastq" || inputType == "pairedFastq") { - - cata("\n") - cata(hpReadout[3], "
    \n") - cata("\n") - cata(hpReadout[8:11], sep="
    \n") - cata("
    \n") - cata("Please check that read percentages are consistent with ") - cata("expectations.
    \n") - -} else if (inputType == "counts") { - - cata("\n") - -} - -cata("The estimated common biological coefficient of variation (BCV) is: ", - commonBCV, "
    \n") - -if (secFactName == "none") { - - cata("No secondary factor specified.
    \n") - -} else { - - cata("Secondary factor specified as: ", secFactName, "
    \n") - -} - -cata("

    Output:

    \n") -cata("PDF copies of JPEGS available in 'Plots' section.
    \n") -for (i in 1:nrow(imageData)) { - if (grepl("barcode", imageData$Link[i])) { - - if (packageVersion("limma")<"3.19.19") { - - HtmlImage(imageData$Link[i], imageData$Label[i], - height=length(selectedGenes)*150) - - } else { - - HtmlImage(imageData$Link[i], imageData$Label[i], - height=length(selectedGenes)*300) - - } - } else { - - HtmlImage(imageData$Link[i], imageData$Label[i]) - - } -} -cata("
    \n") - -cata("

    Differential Representation Counts:

    \n") - -cata("\n") -cata("\n") -TableItem() -for (i in colnames(sigDiff)) { - TableHeadItem(i) -} -cata("\n") -for (i in 1:nrow(sigDiff)) { - cata("\n") - TableHeadItem(unmake.names(row.names(sigDiff)[i])) - for (j in 1:ncol(sigDiff)) { - TableItem(as.character(sigDiff[i, j])) - } - cata("\n") -} -cata("
    ") - -cata("

    Plots:

    \n") -for (i in 1:nrow(linkData)) { - if (grepl(".pdf", linkData$Link[i])) { - HtmlLink(linkData$Link[i], linkData$Label[i]) - } -} - -cata("

    Tables:

    \n") -for (i in 1:nrow(linkData)) { - if (grepl(".tsv", linkData$Link[i])) { - HtmlLink(linkData$Link[i], linkData$Label[i]) - } -} - -cata("

    Alt-click links to download file.

    \n") -cata("

    Click floppy disc icon on associated history item to download ") -cata("all files.

    \n") -cata("

    .tsv files can be viewed in Excel or any spreadsheet program.

    \n") - -cata("

    Additional Information:

    \n") - -if (inputType == "fastq") { - - ListItem("Data was gathered from fastq raw read file(s).") - -} else if (inputType == "counts") { - - ListItem("Data was gathered from a table of counts.") - -} - -if (cpmReq != 0 && sampleReq != 0) { - tempStr <- paste("Target sequences without more than", cpmReq, - "CPM in at least", sampleReq, "samples are insignificant", - "and filtered out.") - ListItem(tempStr) - - filterProp <- round(filteredCount/preFilterCount*100, digits=2) - tempStr <- paste0(filteredCount, " of ", preFilterCount," (", filterProp, - "%) target sequences were filtered out for low ", - "count-per-million.") - ListItem(tempStr) -} - -if (readReq != 0) { - tempStr <- paste("Samples that did not produce more than", readReq, - "counts were filtered out.") - ListItem(tempStr) - - tempStr <- paste0(sampleFilterCount, " samples were filtered out for low ", - "counts.") - ListItem(tempStr) -} - -if (exists("filteredSamples")) { - tempStr <- paste("The following samples were filtered out for having zero", - "library size: ", filteredSamples) - ListItem(tempStr) -} - -if (workMode == "classic") { - ListItem("An exact test was performed on each target sequence.") -} else if (workMode == "glm") { - ListItem("A generalised linear model was fitted to each target sequence.") -} - -cit <- character() -link <-character() -link[1] <- paste0("", "limma User's Guide", ".") -link[2] <- paste0("", "edgeR User's Guide", "") - -cit[1] <- paste("Robinson MD, McCarthy DJ and Smyth GK (2010).", - "edgeR: a Bioconductor package for differential", - "expression analysis of digital gene expression", - "data. Bioinformatics 26, 139-140") -cit[2] <- paste("Robinson MD and Smyth GK (2007). Moderated statistical tests", - "for assessing differences in tag abundance. Bioinformatics", - "23, 2881-2887") -cit[3] <- paste("Robinson MD and Smyth GK (2008). Small-sample estimation of", - "negative binomial dispersion, with applications to SAGE data.", - "Biostatistics, 9, 321-332") - -cit[4] <- paste("McCarthy DJ, Chen Y and Smyth GK (2012). Differential", - "expression analysis of multifactor RNA-Seq experiments with", - "respect to biological variation. Nucleic Acids Research 40,", - "4288-4297") - -cata("

    Citations

    ") -cata("
      \n") -ListItem(cit[1]) -ListItem(cit[2]) -ListItem(cit[3]) -ListItem(cit[4]) -cata("
    \n") - -cata("

    Report problems to: su.s@wehi.edu.au

    \n") - -for (i in 1:nrow(linkData)) { - if (grepl("session_info", linkData$Link[i])) { - HtmlLink(linkData$Link[i], linkData$Label[i]) - } -} - -cata("\n") -cata("\n") -TableItem("Task started at:"); TableItem(timeStart) -cata("\n") -cata("\n") -TableItem("Task ended at:"); TableItem(timeEnd) -cata("\n") -cata("\n") -TableItem("Task run time:"); TableItem(timeTaken) -cata("\n") -cata("
    \n") - -cata("\n") -cata("") diff -r a72211e03b38 -r c1b3da0fde4a hairpinTool.xml --- a/hairpinTool.xml Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,645 +0,0 @@ - - - - for differential representation for shRNAseq and sgRNA - - - - R - shrnaseq_r - HAIRPINTOOL_R_SOURCE - - - - - - - - Rscript \$HAIRPINTOOL_R_SOURCE "$inputOpt.inputType" - #if $inputOpt.inputType=="fastq": - - #for $i, $fas in enumerate($inputOpt.fastq): - fastq::$fas.file - #end for - - "$inputOpt.hairpin" - "$inputOpt.samples" - - #if $inputOpt.positions.posOption=="yes": - $inputOpt.positions.barstart - $inputOpt.positions.barend - 0 - 0 - $inputOpt.positions.hpstart - $inputOpt.positions.hpend - #else: - 1 - 5 - 0 - 0 - 37 - 57 - #end if - #elif $inputOpt.inputType=="pairedFastq": - - #for $i, $fas in enumerate($inputOpt.fastq): - fastq::$fas.file - #end for - - #for $i, $fas in enumerate($inputOpt.fastq): - fastqRev::$fas.fileRev - #end for - - "$inputOpt.hairpin" - "$inputOpt.samples" - - #if $inputOpt.positions.posOption=="yes": - $inputOpt.positions.barstart - $inputOpt.positions.barend - $inputOpt.positions.barstartRev - $inputOpt.positions.barendRev - $inputOpt.positions.hpstart - $inputOpt.positions.hpend - #else: - 1 - 5 - 0 - 0 - 37 - 57 - #end if - - #elif $inputOpt.inputType=="counts": - "$inputOpt.counts" - "$inputOpt.hairpin" - "$inputOpt.samples" - 0 - 0 - 0 - 0 - 0 - #end if - - #if $inputOpt.secondaryFactor.secFactorOpt=="yes": - "$inputOpt.secondaryFactor.secFactName" - #else: - "none" - #end if - - #if $filterCPM.filtOption=="yes": - $filterCPM.cpmReq - $filterCPM.sampleReq - $filterCPM.readReq - #else: - -Inf - -Inf - -Inf - #end if - - "$fdr" - "$lfc" - "$direction" - "$workMode.mode" - "$outFile" - "$outFile.files_path" - - #if $workMode.mode=="classic": - "$workMode.pair1" - "$workMode.pair2" - #elif $workMode.mode=="glm": - "$workMode.contrast" - "$workMode.roast.roastOption" - - #if $workMode.roast.roastOption=="yes": - "$workMode.roast.hairpinReq" - "$workMode.roast.select.selOption" - "$workMode.roast.select.selection" - #else: - 0 - 0 - 0 - #end if - - #end if - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -.. class:: infomark - -**What it does** - -Given tables containing information about the hairpins/sgRNA and their -associated sample indices, information about the samples and fastq file -containing the sequencing reads. This tool will generate plots and tables for -the analysis of differential representation. - -.. class:: infomark - -A tutorial of how to use this tool is available at: -http://bioinf.wehi.edu.au/shRNAseq/galaxy.html - ------ - -.. class:: infomark - -**INPUTS** - -**Input File Type:** - -This tool is able to either generate counts from a raw FastQ file given the -information regarding the samples and hairpins/sgRNA. Alternatively if a table -of counts has already been generated it can also be used. - -**Counts Table (Counts Input):** - -A tab delimited text table of information regarding the counts of -hairpins/sgRNA. Should have a column 'ID' to denote the hairpins/sgRNA that -counts correspond to. Each additional column should have titles corresponding to -the label for the sample. - -Example:: - - ID Sample1 Sample2 Sample3 - Control1 49802 48014 40148 - Control2 12441 16352 14232 - Control3 9842 9148 9111 - Hairpin1 3300 3418 2914 - Hairpin2 91418 95812 93174 - Hairpin3 32985 31975 35104 - Hairpin4 12082 14081 14981 - Hairpin5 2491 2769 2691 - Hairpin6 1294 1486 1642 - Hairpin7 49501 49076 47611 - ... - -**Target Sequence Annotation:** - -A tab delimited text table of information regarding the targetted -hairpins/sgRNA sequence. Should have columns 'ID', 'Sequences' and 'Gene' to -uniquely identify the target, align it with the reads to produce counts and -identify which gene the target acts on. - -NOTE: the column names are case sensitive and should be input exactly as they -are shown here. - -Example:: - - ID Sequences Gene - Control1 TCTCGCTTGGGCGAGAGTAAG 2 - Control2 CCGCCTGAAGTCTCTGATTAA 2 - Control3 AGGAATTATAATGCTTATCTA 2 - Hairpin1 AAGGCAGAGACTGACCACCTA 4 - Hairpin2 GAGCGACCTGGTGTTACTCTA 4 - Hairpin3 ATGGTGTAAATAGAGCTGTTA 4 - Hairpin4 CAGCTCATCTTCTGTGAAGAA 4 - Hairpin5 CAGCTCTGTGGGTCAGAAGAA 4 - Hairpin6 CCAGGCACAGATCTCAAGATA 4 - Hairpin7 ATGACAAGAAAGACATCTCAA 7 - ... - -**Sample Annotation (FastQ Input):** - -A tab delimited text table of information regarding the samples. Should have -columns 'ID', 'Sequences' and 'group' to uniquely identify each sample, identify -the sample in the reads by its sample index sequence and correctly group -replicates for analysis. Additional columns may inserted for annotation purposes -and will not interfere with analysis as long as the necessary columns are -present. - -NOTE: With the exception of other_group, column names are case sensitive and -should be input exactly as they are shown here. The other_group column can be -named by the user and specified in the "Include Secondary Factor" option of the -tool. - -Example:: - - ID Sequences group other_group Replicate - 3 GAAAG Day 2 male 1 - 6 GAACC Day 10 female 1 - 9 GAAGA Day 5 GFP neg male 1 - 16 GAATT Day 5 GFP pos male 1 - 18 GACAC Day 2 female 2 - 21 GACCA Day 10 male 2 - 28 GACGT Day 5 GFP neg male 2 - 31 GACTG Day 5 GFP pos female 2 - 33 GAGAA Day 2 male 3 - 40 GAGCT Day 10 female 3 - ... - -**Include Secondary Factor** - -If there are two factors involved in the experiment (i.e. Age and Gender) then -then secondary factor should be included to improve the statistical analysis. -The secondary factor should be specified as a column in the sample annotation -file and the corresponding column name should be input exactly as it is into -the provided field in the tool. - -NOTE: Currently the secondary factor is used only to improve statistical -analysis, comparisons can only be made in the primary factor specified as -"group" in the sample annotation. - -**Specify Sample Index and Target Sequence Locations (FastQ Input):** - -It is assumed that in the sequencing reads that the first 5 bases are the -sample index sequence and that bases 37-57 are the hairpins/sgRNA. If this is -not the case then the values of the positions can be changed, however it still -requires the sample indices and hairpins/sgRNA to be in a consistent location an -in a continuous sequence. - -NOTE: position values start at 1 for the first base. - -**Filter Low CPM?:** - -Often in a large screen there may members with very low counts which are of no -interest in the experiment, these may be filtered out to speed up computations. -Filtering will be based on counts per million in a required number of samples. - -**Analysis Type:** - - * **Classic Exact Test:** This allows two experimental groups to be compared - and p-values for differential representation derivec for each target - sequence. Simple and fast for straightforward comparisons. In this option you - will have the option of "*Compare* x *To* y" which implicitly subtracts the - data from y from that of x to produce the comparison. - - * **Generalised Linear Model:** This allow for complex contrasts to be specified - and also gene level analysis to be performed. If this option is chosen then - contrasts must be explicitly stated in equations and multiple contrasts can - be made. In addition there will be the option to analyse hairpins/sgRNA on a - per-gene basis to see if hairpins/sgRNA belonging to a particular gene have - any overall tendencies for the direction of their log-fold-change. - -**FDR Threshold:** -The smear plot in the output will have hairpins/sgRNA highlighted to signify -significant differential representation. The significance is determined by -contorlling the false discovery rate, only those with a FDR lower than the -threshold will be highlighted in the plot. - - ------ - - -**Citations:** - -.. class:: infomark - -limma - -Please cite the paper below for the limma software itself. Please also try -to cite the appropriate methodology articles that describe the statistical -methods implemented in limma, depending on which limma functions you are -using. The methodology articles are listed in Section 2.1 of the limma -User's Guide. - - * Smyth, GK (2005). Limma: linear models for microarray data. In: - 'Bioinformatics and Computational Biology Solutions using R and - Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, - W. Huber (eds), Springer, New York, pages 397-420. - -.. class:: infomark - -edgeR - -Please cite the first paper for the software itself and the other papers for -the various original statistical methods implemented in edgeR. See -Section 1.2 in the User's Guide for more detail. - - * Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor - package for differential expression analysis of digital gene expression - data. Bioinformatics 26, 139-140 - - * Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing - differences in tag abundance. Bioinformatics 23, 2881-2887 - - * Robinson MD and Smyth GK (2008). Small-sample estimation of negative - binomial dispersion, with applications to SAGE data. - Biostatistics, 9, 321-332 - - * McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis - of multifactor RNA-Seq experiments with respect to biological variation. - Nucleic Acids Research 40, 4288-4297 - -Report problems to: su.s@wehi.edu.au - -.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html -.. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html - - diff -r a72211e03b38 -r c1b3da0fde4a readme.rst --- a/readme.rst Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,15 +0,0 @@ -shrnaseq wrapper -================ - -This is a self installing Galaxy tool exposing the shrnaseq_ R package which has excellent documentation at -shrnaseq_ Minimal details are provided in this wrapper - please RTM to get the best out of it. - - -.. _shrnaseq: http://bioinf.wehi.edu.au/shRNAseq/ - -Underlying R code written by Matt Ritchie. -Galaxy wrapper by Shian Su -Autoinstallation and fixin' : Ross Lazarus - -This version first passed tests on 18 Jan 2015 - diff -r a72211e03b38 -r c1b3da0fde4a test-data/shrnaseq_zuber_test.html --- a/test-data/shrnaseq_zuber_test.html Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,80 +0,0 @@ - - -EdgeR Output - - -

    EdgeR Analysis Output:

    -

    Input Summary:

    - -The estimated common biological coefficient of variation (BCV) is: 0.9323
    -No secondary factor specified.
    -

    Output:

    -PDF copies of JPEGS available in 'Plots' section.
    -Counts per Index -Counts per Hairpin -MDS Plot -BCV Plot -Smear Plot(Day.0-Day.14) -
    -

    Differential Representation Counts:

    - - - - - - - - - - - - - -
    UpFlatDown
    Day 0-Day 1437668235

    Plots:

    -Counts per Index Barplot (.pdf)
    -Counts per Hairpin Barplot (.pdf)
    -MDS Plot (.pdf)
    -BCV Plot (.pdf)
    -Smear Plot(Day.0-Day.14) (.pdf)
    -

    Tables:

    -Top Tags Table(Day.0-Day.14) (.tsv)
    -Counts table (.tsv)
    -

    Alt-click links to download file.

    -

    Click floppy disc icon on associated history item to download all files.

    -

    .tsv files can be viewed in Excel or any spreadsheet program.

    -

    Additional Information:

    -
  • Data was gathered from a table of counts.
    • -
  • Target sequences without more than 0.5 CPM in at least 1 samples are insignificant and filtered out.
    • -
  • 1 of 1094 (0.09%) target sequences were filtered out for low count-per-million.
    • -
  • Samples that did not produce more than 1000 counts were filtered out.
    • -
  • 0 samples were filtered out for low counts.
    • -
  • An exact test was performed on each target sequence.
    • -

    Citations

      -
    1. Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140
      2. -
    2. Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing differences in tag abundance. Bioinformatics 23, 2881-2887
      3. -
    3. Robinson MD and Smyth GK (2008). Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics, 9, 321-332
      4. -
    4. McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297
      5. -
    -

    Report problems to: su.s@wehi.edu.au

    -Session Info
    - - - - - - - - - - - - - -
    Task started at:2015-01-20 12:16:59
    Task ended at:2015-01-20 12:17:05
    Task run time:6 secs
    - - \ No newline at end of file diff -r a72211e03b38 -r c1b3da0fde4a test-data/zuber-count_matrix.txt --- a/test-data/zuber-count_matrix.txt Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1106 +0,0 @@ -ID Reads_A_T0 Reads_A_T14 Reads_B_T0 Reads_B_T14 -100043305.2 34133 9171 31158 4111 -100043305.4 5589 1 4311 5737 -100043305.5 38651 7722 24711 15331 -2900092E17Rik.377 11759 24 9328 21 -2900092E17Rik.546 3581 30 3211 3 -2900092E17Rik.1051 11498 1907 10809 4116 -2900092E17Rik.1361 5590 1128 5753 1704 -Actl6b.379 8147 3520 8262 3861 -Actl6b.819 7152 5311 7080 2636 -Actl6b.917 3549 3 3326 9 -Actl6b.989 9928 3200 12207 1787 -Actl6b.1221 2449 173 4553 190 -Alkbh2.462 8219 0 8307 3674 -Alkbh2.557 17312 11788 16162 7253 -Alkbh2.590 908 0 3 0 -Alkbh2.640 29881 9982 32507 6981 -Alkbh2.641 30677 31067 21977 5244 -Alkbh3.552 7748 95 10813 628 -Alkbh3.843 7288 47 6161 1141 -Alkbh3.901 11464 10632 13945 986 -Alkbh3.1184 235478 121880 223886 199915 -Aof2.1869 4835 1 6635 18 -Aof2.1956 9168 74 11901 2001 -Aof2.2435 22561 5296 27662 4349 -Aof2.2857 12275 0 13761 0 -Ash1l.1031 40881 12818 35694 11615 -Ash1l.1280 15907 3501 24446 2818 -Ash1l.3810 0 0 570 0 -Ash1l.8132 16135 3240 13553 8157 -Ash1l.9540 19334 4915 19956 482 -Ash2l.586 17315 3908 16296 11351 -Ash2l.805 15308 11745 19785 7504 -Ash2l.948 17154 7175 22222 1182 -Ash2l.1135 10872 23 9514 649 -Ash2l.2130 48820 71306 54356 55586 -Asxl1.2020 8883 85 7366 810 -Asxl1.3548 1499 177 4290 434 -Asxl1.3785 13925 9770 13967 1888 -Asxl1.4792 14695 2973 17368 6663 -Asxl1.5221 207 21 1015 413 -Asxl1.6315 5323 2931 4104 1254 -Asxl2.11 12636 1202 19230 836 -Asxl2.4563 6740 9470 6275 14168 -Asxl2.6593 7040 7865 7327 463 -Asxl2.7130 1005 688 1998 98 -Asxl2.7253 2848 0 4313 1015 -Asxl3.6101 27880 9120 23317 9903 -Asxl3.6824 0 0 0 0 -Asxl3.8947 10505 1283 17111 8040 -Asxl3.10021 11150 77 9094 418 -Asxl3.11070 6878 434 13876 499 -Asxl3.11073 19570 60 23697 1250 -Atm.137 7726 1 7961 0 -Atm.4098 17664 79096 14372 19643 -Atm.4998 5448 0 8348 0 -Atm.5616 26499 17417 25957 5963 -Atm.7782 121694 37584 112860 23911 -Atm.9396 23098 8301 16153 13589 -Atr.1239 7318 0 7499 76 -Atr.3160 4630 0 2454 0 -Atr.4762 7087 502 6196 1408 -Atr.6186 14186 1517 14242 2136 -Atr.7888 2705 715 1274 40 -Atrx.2490 21802 13082 20344 3929 -Atrx.5490 9146 4876 8110 1459 -Atrx.6144 22072 50037 17635 135473 -Atrx.7173 20760 2010 32941 360 -Atrx.7377 4661 7127 5894 858 -Aurkb.520 10448 158 8464 14 -Aurkb.631 12294 13088 16774 9788 -Aurkb.917 9721 85 7381 297 -Aurkb.928 3823 0 3360 70 -Aurkb.1620 2783 0 1689 0 -Aurkb.1803 5485 964 6727 502 -Baz1a.2095 17890 6381 16476 10861 -Baz1a.2451 8018 26337 7113 7350 -Baz1a.4993 4040 2049 5627 4388 -Baz1a.5946 8518 471 7167 756 -Baz1b.801 3377 3 2560 1 -Baz1b.3683 19598 1361 14007 9115 -Baz1b.5646 7619 140 6540 93 -Baz1b.6371 20503 0 14675 4199 -Bmi1.698 13315 927 12090 1400 -Bmi1.895 22321 1589 22783 0 -Bmi1.1440 148 0 1337 0 -Bmi1.1746 57319 7041 58914 6748 -Bmi1.2404 2012 0 5750 0 -Bmi1.2561 7381 4663 6301 1752 -Bop1.778 22193 9880 25011 22498 -Bop1.2228 9126 1164 11243 1759 -Bop1.2403 1267 0 2340 0 -Bptf.1622 19917 1645 16672 1194 -Bptf.3234 29927 1975 29930 1459 -Bptf.7211 9162 196 8435 235 -Bptf.8224 22786 4089 25881 16627 -Braf.3750 251680 111577 252403 96275 -Braf.3826 36692 6171 38833 3552 -Braf.5053 21572 58690 24272 47962 -Brd1.286 2667 1 3889 732 -Brd1.287 47567 32364 42739 11998 -Brd1.2096 15510 483 12893 662 -Brd1.4229 1776 47 2985 0 -Brd2.813 8544 364547 19761 57153 -Brd2.1714 7605 1900 7256 279 -Brd2.3011 1335 40 1645 44 -Brd2.3396 447 431 1478 90 -Brd3.187 20291 0 16080 1 -Brd3.298 45100 2627 41908 2295 -Brd3.411 3322 4993 9122 88 -Brd3.4162 4380 3233 4235 2236 -Brd4.523 59871 250 62100 1030 -Brd4.552 4366 0 4085 0 -Brd4.632 6519 0 8625 0 -Brd4.1448 18590 2201 13467 2049 -Brd4.2097 15250 0 12300 0 -Carm1.892 7893 3 7502 1189 -Carm1.1222 6127 0 5712 860 -Carm1.1454 6356 0 4529 0 -Carm1.1614 2578 0 2116 1032 -Carm1.1717 10432 26 5147 5 -Cbx1.1004 2119 176 2118 68 -Cbx1.1053 55760 32885 49270 78522 -Cbx1.1099 6839 6288 10338 2367 -Cbx1.1103 16450 2350 10274 7958 -Cbx1.1210 4161 1553 6473 768 -Cbx2.2033 3805 6 3394 910 -Cbx2.3537 1236 0 1822 0 -Cbx2.3545 1510 1926 1608 235 -Cbx2.3620 4720 41 4982 1298 -Cbx2.3706 15664 23374 12341 9903 -Cbx3.882 3121 0 3119 0 -Cbx3.1206 13461 1774 17078 1812 -Cbx3.1339 19195 1352 22424 4795 -Cbx3.1719 4977 0 5860 0 -Cbx3.1735 20825 237 16087 3528 -Cbx4.1794 9233 3426 6939 16366 -Cbx4.1844 2832 3464 4193 744 -Cbx4.2573 69888 62259 67617 50333 -Cbx4.4403 3806 0 4281 1847 -Cbx4.5120 11707 4670 9880 5888 -Cbx5.1309 20635 20130 21845 21774 -Cbx5.4366 907 0 563 0 -Cbx5.4409 9565 1475 14591 3062 -Cbx5.4508 26823 20517 26002 16192 -Cbx5.5707 3839 488 2459 831 -Cbx5.8586 2634 924 4578 8 -Cbx6.1535 1684 44 2014 5254 -Cbx6.3332 32724 36460 41754 5931 -Cbx6.3473 1027 199 1093 2766 -Cbx6.3969 25243 20256 20037 7607 -Cbx7.745 41390 8417 44824 10473 -Cbx7.1633 9110 0 7318 594 -Cbx7.1634 8492 1 7765 1175 -Cbx7.1639 3050 380 4027 305 -Cbx7.2006 12881 0 11203 1803 -Cbx7.2504 15650 74 14065 1023 -Cbx8.136 14429 562 10096 1833 -Cbx8.1120 23518 5129 18818 4414 -Cbx8.1342 91120 117507 88227 77242 -Chaf1a.166 7650 0 8656 0 -Chaf1a.1039 1166 0 1879 0 -Chaf1a.2122 36245 25317 42693 4155 -Chaf1b.367 1271 0 3122 0 -Chaf1b.566 5644 2726 6501 805 -Chaf1b.692 8344 4791 14305 0 -Chaf1b.901 11840 1680 10452 2885 -Chaf1b.1223 3527 0 4039 327 -Chd1.746 42149 4740 47141 5029 -Chd1.1103 9539 301 10681 317 -Chd1.2443 9033 998 8891 1151 -Chd1.2959 17519 3663 17844 3550 -Chd1.4558 16095 18060 18409 694 -Chd1l.2305 13833 2232 9271 1687 -Chd1l.2598 2003 4 3653 467 -Chd1l.2804 8186 1848 9889 4110 -Chd2.926 12754 2298 14491 1390 -Chd2.3700 18791 8160 17139 6180 -Chd2.3984 39660 3183 28160 5299 -Chd2.8087 21625 5699 19522 2258 -Chd2.8913 44266 4697 48691 2032 -Chd3.482 5654 84 2967 437 -Chd3.3249 18194 209 16629 2181 -Chd3.4011 12016 5122 15608 2384 -Chd3.6496 8188 250 11414 658 -Chd3.7148 6057 11694 5216 14343 -Chd3.7149 18779 2183 20787 4073 -Chd4.2060 3613 0 9449 3 -Chd4.3326 0 0 0 0 -Chd4.3423 18147 329 24617 1474 -Chd4.3772 18305 1967 17413 13691 -Chd5.2301 20061 34429 23079 1480 -Chd5.2900 8518 12121 8113 23821 -Chd5.5471 16812 135 14891 832 -Chd5.6392 27664 42408 24064 32029 -Chd6.311 5183 30 4482 283 -Chd6.4698 11850 691 9494 952 -Chd6.4988 9782 9443 8227 3677 -Chd6.9610 4646 4252 7143 2341 -Chd7.1269 5308 36016 5596 15544 -Chd7.1502 17568 19902 24339 10329 -Chd7.5857 24131 42321 23035 13811 -Chd7.6498 2585 2388 3680 681 -Chd7.7229 4726 3715 3325 5096 -Chd8.434 10501 5059 13580 0 -Chd8.3265 14017 45094 15274 35713 -Chd8.4169 46755 130786 47380 90425 -Chd8.5352 15081 0 10249 963 -Chd8.6946 24933 3532 29506 678 -Chd9.1402 8846 10701 5390 15209 -Chd9.3919 30650 5485 31316 8951 -Chd9.9352 4541 7 4353 547 -Chd9.10928 11786 846 6533 3211 -Clock.693 30386 192421 30632 61226 -Clock.1387 3512 16 6185 1879 -Clock.4461 8821 15720 13658 32530 -Clock.4611 7531 1868 7634 960 -Clock.5863 8924 0 6154 0 -Crebbp.704 6954 132149 5748 28129 -Crebbp.2064 15054 21613 9232 8683 -Crebbp.2118 16858 416 14067 1155 -Crebbp.3582 10871 49874 11472 31243 -Crebbp.4463 10735 244297 8756 87465 -Ctsl.940 64046 40415 67042 33661 -Ctsl.1445 4304 11403 6955 921 -Ctsl.1941 14957 114 9881 1230 -Ctsl.1942 3801 651 5404 119 -Ctsl.1947 83104 55376 79952 45160 -Cxxc1.68 22254 7624 21861 13433 -Cxxc1.359 16364 0 14694 712 -Cxxc1.1889 13048 105 15103 1803 -Cxxc1.2034 10733 2431 11257 5220 -Cxxc1.2133 24632 4890 18850 3756 -Dmap1.439 22069 17051 18179 11546 -Dmap1.518 270 6 835 0 -Dmap1.1354 27540 2702 27126 5348 -Dmap1.1355 38236 3410 25053 19190 -Dmap1.1487 16458 35264 12204 7974 -Dnmt1.437 2774 1 4466 1933 -Dnmt1.828 37302 0 37771 2350 -Dnmt1.1137 1982 0 900 0 -Dnmt1.4462 19205 1622 19314 2525 -Dnmt1.4848 11770 53612 13284 12279 -Dnmt3a.16 28736 52935 39231 63096 -Dnmt3a.1669 7497 2055 9359 279 -Dnmt3a.2338 26093 14264 21886 8356 -Dnmt3a.4173 90754 147980 91811 371738 -Dnmt3b.275 2759 0 4350 967 -Dnmt3b.579 23800 2457 15840 4413 -Dnmt3b.958 18118 1831 14535 41 -Dnmt3b.2218 4817 0 5321 0 -Dnmt3l.306 1360 0 7206 133 -Dnmt3l.760 107789 89964 109791 48867 -Dnmt3l.1049 12911 3759 16355 4238 -Dnmt3l.1333 10696 5884 9512 8646 -Dnmt3l.1350 11998 13780 13122 7740 -Dot1l.602 15468 1611 18782 28 -Dot1l.941 308 0 1 0 -Dot1l.3626 1819 0 2461 0 -Dub2a.769 20173 45614 27227 22193 -Dub2a.1334 3322 913 3054 1061 -Dub2a.1391 7400 0 6144 0 -Dub2a.1397 1989 1475 2177 2420 -Dub2a.1444 6000 772 9736 1277 -Dub2a.1445 17909 5522 13925 4446 -Edf1.486 21827 12951 27904 16057 -Edf1.628 14218 14904 9199 1968 -Edf1.631 17016 5000 14264 1849 -Edf1.652 14581 2743 14121 1112 -Eed.710 5375 0 4431 0 -Eed.949 19036 15171 17602 11188 -Eed.1083 40824 1687 39480 698 -Eed.1397 27933 4138 25394 8774 -Eed.1820 36795 99609 29844 5995 -EG330129.869 2661 61 1902 619 -EG330129.2118 14758 1039 18080 5314 -EG330129.2262 15426 19116 20410 28859 -EG330129.2329 19693 6224 15507 1799 -EG546387.1344 61423 132971 65502 105110 -EG546387.2159 18532 5441 17522 6441 -EG546387.2272 5181 2230 3858 1293 -Ehmt1.66 23038 3862 34576 8831 -Ehmt1.386 78913 8990 88361 18872 -Ehmt1.859 3728 0 2265 0 -Ehmt1.920 12674 47588 15786 8109 -Ehmt1.3003 17009 4 13764 0 -Ehmt2.724 28567 15002 19363 7218 -Ehmt2.1880 16161 724 10956 2142 -Ehmt2.2014 9586 2303 10876 5893 -Ehmt2.3146 20606 4947 20381 4673 -Ehmt2.3202 12157 924 12076 0 -Elp3.117 13584 1649 11794 7368 -Elp3.215 14727 1372 14790 23 -Elp3.219 17103 125 19102 1933 -Elp3.592 7651 1 13554 437 -Ep300.754 49982 34746 48931 26824 -Ep300.3850 4229 0 4817 0 -Ep300.5490 19810 2485 18297 1698 -Ep300.7826 25198 3046 25177 307 -Ep300.8647 34570 13119 36600 5763 -Evi1.649 23821 1022 23583 938 -Evi1.652 4938 1433 6371 7108 -Evi1.1371 6351 4198 5211 3390 -Evi1.1978 0 0 0 0 -Evi1.2720 8079 4150 7301 4240 -Ezh1.68 23617 6527 29619 30045 -Ezh1.73 2152 1 2857 3113 -Ezh1.4104 5575 74 3572 1105 -Ezh1.4105 10809 0 9427 3236 -Ezh2.556 5195 3183 2808 898 -Ezh2.1370 13095 1 16542 4081 -Ezh2.1678 39634 33392 36467 37036 -Ezh2.2124 24614 13542 24923 1861 -Ezh2.2253 23466 844 25517 49 -Fbxl10.356 9135 6792 12154 10033 -Fbxl10.443 1186 0 1217 0 -Fbxl10.3131 12157 3918 15296 5301 -Fbxl10.3145 28882 145367 25071 266575 -Fbxl11.663 4479 254 4500 248 -Fbxl11.1840 2254 1230 892 701 -Fbxl11.7144 14494 9088 14709 3408 -Fbxl11.7145 10143 70 8133 314 -Fbxl19.1945 4994 4 6347 0 -Fbxl19.2841 4416 0 3763 0 -Fbxl19.3203 17900 0 21153 395 -Fkbp1a.646 7663 6 6272 169 -Fkbp1a.827 3731 66420 5825 4725 -Fkbp1a.851 2142 4 1255 0 -Fkbp1a.854 17779 5211 17456 2979 -Fkbp2.195 12182 84 7562 997 -Fkbp2.213 1713 0 1042 0 -Fkbp2.532 190 0 104 0 -Fkbp2.581 29896 2210 38434 3532 -Fkbp5.595 6187 1738 9425 3732 -Fkbp5.628 2539 448 2028 4 -Fkbp5.1219 2462 0 1697 3 -Fkbp5.2613 0 0 0 0 -Fkbp5.2813 27937 0 19923 52176 -Fkbp5.3272 7148 720 11556 616 -Gtf3c4.2358 14364 7409 14531 1446 -Gtf3c4.2444 5365 106 8597 3468 -Gtf3c4.2605 13187 44260 17871 32768 -Gtf3c4.3160 12285 1919 9387 2634 -Gtf3c4.3163 23210 21932 22233 10393 -H2afz.508 7648 1460 7024 236 -H2afz.692 13424 1472 13562 1762 -H2afz.823 8678 0 5225 0 -H2afz.909 27579 108855 26279 31357 -H2afz.937 6529 1591 6908 1939 -Hat1.290 40899 11691 48020 9574 -Hat1.638 278838 398517 279877 354180 -Hat1.866 13651 10058 10447 5453 -Hat1.1528 5921 3024 8953 2868 -Hcfc1.812 28786 4502 27161 4598 -Hcfc1.4648 8357 0 9882 1262 -Hcfc1.7430 4307 160 3200 35 -Hcfc1.7506 43003 8634 44678 2972 -Hcfc1.8014 8845 33 9753 0 -Hdac1.245 4808 1777 5428 576 -Hdac1.1053 15708 11064 13398 2392 -Hdac1.1065 6119 41 4640 0 -Hdac1.1830 10309 3420 7166 15784 -Hdac10.1645 0 0 0 0 -Hdac10.2041 9421 30 13575 906 -Hdac10.2307 11332 4605 15942 1310 -Hdac11.2025 5748 390 4388 1 -Hdac11.2058 21979 11670 33308 23388 -Hdac11.2182 2741 0 1897 0 -Hdac11.2460 3150 226 3435 986 -Hdac11.2461 5426 792 5499 365 -Hdac2.439 29909 2942 35230 5020 -Hdac2.440 1162 0 1339 0 -Hdac2.1184 19432 33612 18548 32335 -Hdac2.1611 39116 35275 44610 9355 -Hdac2.1919 58543 16034 62733 11276 -Hdac3.161 5438 284 5431 16 -Hdac3.854 11512 3613 11530 925 -Hdac3.987 15606 236696 17908 57900 -Hdac3.1037 4439 1723 4619 0 -Hdac3.1491 7985 0 6286 986 -Hdac4.331 16436 6934 19062 1466 -Hdac4.431 6765 158440 9201 22187 -Hdac4.1903 1357 657 1195 991 -Hdac4.3273 14916 944 19717 2146 -Hdac5.1115 2098 613 2229 0 -Hdac5.1936 18798 7849 29847 6138 -Hdac5.2060 2568 3 1204 121 -Hdac5.2412 13712 1 11404 3505 -Hdac5.2886 8136 196 8759 209 -Hdac6.530 0 0 0 0 -Hdac6.2249 1808 1429 2043 0 -Hdac6.3838 6542 2441 9262 5129 -Hdac6.4026 21285 12348 26787 20564 -Hdac7.560 6870 687 6840 0 -Hdac7.836 8926 5421 7502 10495 -Hdac7.1293 34937 9117 34192 6997 -Hdac7.2255 20876 6721 30076 1172 -Hdac7.3429 5979 454 5696 805 -Hdac8.296 1838 0 3737 0 -Hdac8.397 13492 5078 9430 2980 -Hdac8.900 25917 1733 29902 2130 -Hdac8.1692 22304 21086 26207 12759 -Hdac9.1236 8992 519 14512 952 -Hdac9.1449 12626 676 13666 458 -Hdac9.2031 17918 4808 17044 2570 -Hdac9.2070 59653 6259 56073 20783 -Hdac9.4083 45586 22853 43689 11794 -Hells.977 1299 1 2614 2157 -Hells.1094 0 0 0 0 -Hells.1145 31010 2668 28532 1538 -Hells.1703 9030 9859 5844 8448 -Hells.2323 35114 5146 32398 1612 -Hira.223 8759 417 7043 211 -Hira.2318 7426 0 9835 0 -Hira.2835 4556 12145 5932 4706 -Hira.4298 8683 101 5451 536 -Hltf.252 20489 11041 22885 6226 -Hltf.455 76855 45338 80380 23580 -Hltf.497 25307 38142 24907 146870 -Hltf.1198 3863 153 3035 1096 -Ing2.649 4504 6 4733 244 -Ing2.1400 38848 18868 29144 11601 -Ing2.1788 6201 57 10102 11 -Ing2.1824 10033 3283 10696 1439 -Ing2.2176 29600 1073 32782 6050 -Ino80.458 10511 6016 22774 33294 -Ino80.1194 11000 6405 9044 10376 -Ino80.2062 52365 148689 44701 184145 -Ino80.4069 6702 28691 4415 24593 -Jarid1a.2826 18278 6403 18014 2648 -Jarid1a.6729 10355 5540 10379 22760 -Jarid1a.10299 26860 6487 19211 5470 -Jarid1a.10802 3533 0 4344 926 -Jarid1a.11640 35567 17366 33011 4446 -Jarid1b.382 9868 2723 5159 527 -Jarid1b.1671 0 0 6 0 -Jarid1b.2176 0 0 0 0 -Jarid1b.4339 5073 345 5343 1689 -Jarid1b.4527 9425 50 10059 1381 -Jarid1c.1882 2549 17 3478 953 -Jarid1c.1886 14749 7706 12323 10740 -Jarid1c.2010 2273 2461 527 398 -Jarid1c.5632 27259 49235 24893 11026 -Jarid1d.2138 9206 228 12341 0 -Jarid1d.2800 10754 10630 12462 2316 -Jarid1d.3002 2007 136 2996 282 -Jarid1d.4830 34435 12167 32548 13433 -Jarid2.1699 2892 775 5944 278 -Jarid2.2191 83425 340442 85527 65202 -Jarid2.3219 2395 0 769 0 -Jhdm1d.2087 29857 12371 32979 3416 -Jhdm1d.2209 25750 14116 21403 14704 -Jhdm1d.3273 119204 22930 121764 31402 -Jhdm1d.6787 5686 477 5135 953 -Jhdm1d.8524 30018 8410 33250 9317 -Jmjd1a.371 15143 0 9975 0 -Jmjd1a.753 10118 74 13083 677 -Jmjd1a.1070 5348 0 5622 948 -Jmjd1a.3518 4726 1 5434 5389 -Jmjd1b.1014 22703 16785 20694 20823 -Jmjd1b.3708 4995 0 7649 4 -Jmjd1b.5309 9434 3183 7204 5711 -Jmjd1b.6406 42972 40465 40110 68843 -Jmjd1b.6504 10265 1777 9964 9327 -Jmjd1c.649 9093 1476 8029 3525 -Jmjd1c.3196 6525 11 11473 0 -Jmjd1c.4221 26638 2833 27602 2788 -Jmjd1c.6050 16745 9264 17779 16014 -Jmjd1c.6346 19323 3230 17970 5289 -Jmjd2a.424 4205 508 3711 1090 -Jmjd2a.663 14302 1084 16049 2421 -Jmjd2a.1474 9697 27 8804 1545 -Jmjd2a.1498 66057 4568 55742 948 -Jmjd2a.3033 10638 11 7955 5 -Jmjd2b.1151 13663 16056 13831 9568 -Jmjd2b.2905 112806 268376 97185 116026 -Jmjd2b.4018 5645 5932 6977 11481 -Jmjd2b.4170 28332 10072 26581 38183 -Jmjd2c.738 14473 1738 13755 3513 -Jmjd2c.1217 9829 9470 11148 18647 -Jmjd2c.3112 18781 8790 19860 7108 -Jmjd2c.3541 40250 22412 40729 16482 -Jmjd2d.301 3043 1 3782 975 -Jmjd2d.450 1036 1 3009 8145 -Jmjd2d.1143 7706 7367 7416 180 -Jmjd2d.2310 102210 26240 106864 7826 -Jmjd2d.2358 12130 911 13293 582 -Jmjd4.1722 8159 6247 16741 12010 -Jmjd4.1796 9253 1514 7118 1684 -Jmjd4.2677 31423 25789 37642 20063 -Jmjd4.2749 5793 223 8612 2395 -Jmjd4.3327 23522 4354 26494 24409 -Jmjd5.18 14793 55385 14988 21455 -Jmjd5.1123 5430 203 5612 1456 -Jmjd5.1291 5179 2109 3752 1488 -Jmjd5.1564 10552 237 12059 4238 -Jmjd5.2041 10418 167 7459 9 -Jmjd6.254 13534 2503 11700 729 -Jmjd6.530 3656 97 3885 1044 -Jmjd6.956 11018 2874 16364 76 -Jmjd6.1633 37602 9544 39980 9096 -Kat2a.542 3504 3297 5800 1718 -Kat2a.1771 1161 0 2203 533 -Kat2a.2053 12866 1384 10067 9758 -Kat2a.2201 6827 1761 8972 241 -Kat2b.1306 37105 2671 31383 275 -Kat2b.2624 16637 1228 15500 1335 -Kat2b.3228 6549 413 12258 933 -Kat2b.3494 138189 63210 110981 31184 -Kat2b.3766 16379 2391 10353 790 -Kat5.679 2739 630 2249 10 -Kat5.1193 1796 4824 2367 4568 -Kat5.1242 54 7231 887 4382 -Kat5.1387 15408 52911 10253 43152 -L3mbtl.263 5757 4 5207 2071 -L3mbtl.373 7879 3266 8067 1344 -L3mbtl.725 125876 41968 136893 60944 -L3mbtl.1906 7657 184 3595 0 -L3mbtl.2689 8264 1127 4854 0 -LOC100040412.49 44628 9676 40349 10227 -LOC100040412.495 518 0 264 0 -LOC100040412.655 36670 7127 34829 20101 -LOC100040412.1128 20338 7124 19461 5684 -LOC100044324.736 53916 28423 51151 28391 -LOC100044324.927 3794 1326 5898 0 -LOC100044324.1075 4055 23211 2907 8855 -LOC100044324.1240 3549 0 2335 1159 -LOC100044324.1314 33932 4960 43503 12431 -LOC100048887.186 11625 42693 11686 68360 -LOC100048887.194 1209 0 631 0 -LOC100048887.732 19420 2151 23621 922 -LOC100048887.787 5608 0 5382 0 -LOC100048887.803 15555 1240 14130 2172 -LOC664892.1494 15416 9985 16994 8314 -LOC664892.1500 39567 45154 32681 16788 -LOC664892.1697 21861 3459 23168 13194 -LOC664892.1892 7530 197 9165 1433 -LOC664892.2169 2728 61 694 1 -Mbd1.746 18613 7 15420 5997 -Mbd1.1387 16462 697 11111 3994 -Mbd1.1856 16551 180 18694 2741 -Mbd1.2237 4287 58 3734 1034 -Mbd2.938 18282 0 20638 1385 -Mbd2.1117 57023 25500 68767 7293 -Mbd2.1545 5545 1123 2169 11 -Mbd2.1763 14932 21 8532 469 -Mbd2.1823 168962 47694 166843 91277 -Mbd3.579 2471 28 4469 298 -Mbd3.1147 7558 998 6411 846 -Mbd3.1354 9463 348 9133 333 -Mbd3.1452 12302 19001 10776 2107 -Mbd3.1551 14684 4138 13756 10 -Mbd4.434 7882 186 5141 7256 -Mbd4.1027 26878 5949 31423 2532 -Mbd4.3297 63441 53173 49261 23120 -Mbd4.3541 13769 9186 15004 2583 -Mds1.87 13597 54 10811 997 -Mds1.651 24891 3300 20814 10559 -Mds1.764 6774 13 12423 800 -Mds1.874 55777 60096 65359 33264 -Mecp2.1627 2211 613 2915 114 -Mecp2.2287 30878 16895 24540 25052 -Mecp2.5438 17574 6850 16734 5558 -Mecp2.7745 6981 74 8337 543 -Men1.219 36152 6676 36421 2180 -Men1.228 2413 0 1031 0 -Men1.1457 24003 1418 19287 0 -Men1.2310 1903 0 1963 0 -Men1.2707 3891 0 3747 611 -Mettl8.846 15269 32248 20256 25007 -Mettl8.1184 31695 23070 27103 9050 -Mettl8.1353 13590 3829 7213 1318 -Mettl8.1914 4626 23 2666 1515 -Mettl8.1990 17582 111 13919 1630 -Mgmt.384 8858 14 13506 2427 -Mgmt.412 47142 206140 56921 427295 -Mgmt.433 7563 4297 6613 3666 -Mgmt.672 1225 43 2941 9 -Mgmt.730 22753 5741 18956 3166 -Mll1.4195 19468 5469 15618 2029 -Mll1.11050 22877 942 24834 3541 -Mll1.13303 305 0 759 0 -Mll1.16168 27703 4104 31277 1745 -Mll2.4285 5216 13928 5210 10868 -Mll2.5430 13067 5975 9114 3637 -Mll2.6153 2237 9263 2642 15030 -Mll2.11374 33723 759803 28105 234314 -Mll2.12943 46826 232154 42025 455810 -Mll3.1099 1138 4199 1813 883 -Mll3.2993 19133 11678 12182 9160 -Mll3.5304 3633 0 5156 0 -Mll3.6232 5828 17022 8940 6153 -Mll3.15396 40315 309338 50764 123575 -Morf4l1.281 17414 4324 22313 707 -Morf4l1.603 25422 1074 19962 410 -Morf4l1.639 20761 2921 15916 1451 -Morf4l1.1034 25865 152 27963 287 -Morf4l1.1245 18488 9450 19247 3840 -Mta1.213 1640 0 2028 0 -Mta1.1003 8419 1279 7201 4263 -Mta1.1053 12543 1219 13119 1381 -Mta1.1147 23472 14298 19777 22940 -Mta1.1363 94 0 210 0 -Mta2.511 10088 35 14741 766 -Mta2.924 9090 194 12773 126 -Mta2.1284 16460 7126 14805 1384 -Mta2.2013 126 0 1746 0 -Mta3.222 2387 0 3939 0 -Mta3.553 11839 40 9230 1181 -Mta3.1523 22093 18940 27171 9881 -Mta3.1663 12142 1439 13022 226 -Myst1.643 5812 0 6117 0 -Myst1.724 11510 1026 23724 15872 -Myst1.1250 5525 0 3597 0 -Myst1.1302 4909 220 4468 925 -Myst2.176 84001 121101 82269 41547 -Myst2.507 41910 84241 52804 161235 -Myst2.1183 7207 9429 5826 3312 -Myst2.3099 21920 6172 21876 2265 -Myst3.2590 690 0 1102 0 -Myst3.3127 3786 0 2861 0 -Myst3.3485 1716 21 1398 0 -Myst3.4554 15670 12777 11421 13526 -Myst3.6844 27947 10469 26576 30244 -Myst4.3568 12141 2967 3110 302 -Myst4.5452 16472 24567 19154 12044 -Myst4.6527 15970 3067 14141 2193 -Myst4.6644 21694 44024 22142 61368 -Nap1l1.2360 20442 8951 22291 4467 -Nap1l1.2470 15228 13610 16118 71731 -Nap1l1.3414 33493 21016 37336 5837 -Nap1l1.3554 19656 2232 17595 1953 -Nap1l2.819 18185 14552 18837 65021 -Nap1l2.1093 12286 230 9099 1446 -Nap1l2.1180 7721 1 10120 0 -Nap1l2.1695 13192 395 15216 2247 -Nap1l2.1750 11527 1977 12730 355 -Nap1l3.743 11414 34902 10526 15256 -Nap1l3.779 10585 453392 13704 246034 -Nap1l3.1969 48200 1958 40917 2939 -Nap1l3.2063 5157 569 6952 6 -Nap1l3.2498 4447 43 2318 8 -Ncoa3.1032 13841 5149 15348 10926 -Ncoa3.3669 17643 5797 12819 13390 -Ncoa3.3815 6003 0 4303 512 -Ncoa3.3885 8252 1 7232 527 -Ncoa3.7494 3221 14 3092 724 -Nr0b2.381 11504 6 9099 734 -Nr0b2.534 10457 1255 8156 3874 -Nr0b2.558 19364 2303 17410 2131 -Nr0b2.1023 42733 48641 39109 13800 -Nr0b2.1068 58582 99191 69312 43078 -Nsd1.2795 0 0 415 238 -Nsd1.5598 21387 11162 17611 11484 -Nsd1.5640 22756 21 29222 334 -Nsd1.11634 6488 299 4923 3308 -Padi4.295 15624 4046 18150 408 -Padi4.1042 11140 5914 7592 9678 -Padi4.1058 7187 2580 9327 5213 -Padi4.1914 6051 2929 7850 1 -Padi4.2336 5954 352 8032 523 -Parp1.1124 10502 3860 10456 567 -Parp1.1623 4986 938 4516 94 -Parp1.2887 4108 1300 4481 6581 -Parp1.3789 15343 453 14110 13 -Parp1.3790 22972 7864 22581 8646 -Parp2.574 20473 250 12332 0 -Parp2.905 3913 1940 6975 0 -Parp2.946 8940 952 6587 0 -Parp2.1006 12735 20094 9708 16966 -Parp2.1429 3923 1209 1909 54 -Parp2.1677 21429 365 15745 701 -Pax5.154 7895 1858 7788 681 -Pax5.328 7916 3945 8084 2341 -Pax5.601 16755 412 16181 1171 -Pax5.852 5606 43539 6945 80501 -Pax5.914 7880 237 9620 2649 -Paxip1.3203 41990 12756 45697 3247 -Paxip1.3451 21718 77708 22111 91808 -Paxip1.3562 16353 10026 16730 13912 -Paxip1.3670 36342 334247 43757 46048 -Pcgf2.507 23232 7601 27671 10380 -Pcgf2.690 8265 1327 6110 49 -Pcgf2.801 18514 1270 22113 2903 -Pcgf2.982 33166 12751 28473 14390 -Pcgf2.1013 17638 1 20019 3606 -Pcmt1.619 18240 43248 19763 17914 -Pcmt1.620 3869 1 8380 1106 -Pcmt1.840 23942 591737 28292 852487 -Pcmt1.946 7092 2887 7370 7007 -Pcmt1.1259 36457 29451 34007 14026 -Pcna.566 57814 1239 48176 293 -Pcna.1186 22524 0 21335 0 -Phf1.561 29733 32867 26321 1012 -Phf1.637 24740 11373 12636 2567 -Phf1.1098 6665 1228 6817 360 -Phf1.2400 13673 2799 11408 1727 -Phf2.1851 16125 7502 17489 1720 -Phf2.3668 3941 7 3400 2394 -Phf2.5132 46204 31225 41687 56982 -Phf2.5166 49720 28142 45140 127055 -Phf8.1420 44092 22623 45369 25710 -Phf8.1984 25612 1565 21593 2593 -Phf8.2131 11570 480 6245 3 -Polr2b.489 4441 0 3338 0 -Polr2b.2176 14171 1 16062 0 -Ppargc1a.669 8229 7478 10179 1715 -Ppargc1a.831 221 0 257 0 -Ppargc1a.1269 34453 15023 26676 10184 -Ppargc1a.1500 20357 4144 22189 5681 -Prdm1.711 7594 136 12326 1021 -Prdm1.862 13674 1272 17495 2820 -Prdm1.919 7981 211 6452 659 -Prdm1.2964 9702 1649 6519 74 -Prdm1.3709 6880 2963 4367 6545 -Prdm10.318 38326 1624 35774 3435 -Prdm10.1130 22199 3710 18678 2910 -Prdm10.1348 14385 2569 11194 719 -Prdm10.2613 9338 5136 8248 0 -Prdm11.1844 7683 26 9378 903 -Prdm11.2306 2693 505 1394 36 -Prdm11.3215 34411 12308 45331 6294 -Prdm11.3216 9073 928 6858 1530 -Prdm12.481 11080 1 8398 2032 -Prdm12.603 18533 2716 14848 1285 -Prdm12.1421 11165 13 7190 522 -Prdm12.2351 35983 35549 39030 28743 -Prdm13.554 6553 145 6306 626 -Prdm13.2613 24026 74465 26691 198619 -Prdm13.2702 1483 0 964 1006 -Prdm13.2828 21409 2400 19712 753 -Prdm13.2936 20674 4192 24072 8085 -Prdm14.530 6054 2386 6453 2689 -Prdm14.1756 2872 0 3280 39 -Prdm14.1934 1736 915 2137 128 -Prdm14.2271 23286 2272 18192 2265 -Prdm14.2348 4410 186 4574 4312 -Prdm15.958 948 1832 1351 44 -Prdm15.1034 7500 28 7058 31 -Prdm15.1690 11098 4766 8877 5507 -Prdm15.1796 18603 3415 17010 2809 -Prdm15.2734 6593 26 11491 850 -Prdm16.680 27382 18093 23775 9678 -Prdm16.5683 9804 1774 12654 158 -Prdm16.8212 510 0 75 0 -Prdm16.8363 32959 8200 37005 22671 -Prdm16.8571 41183 105040 34452 72617 -Prdm2.1020 5835 1513 6535 313 -Prdm2.4191 17204 8644 12039 7427 -Prdm2.4655 0 0 0 0 -Prdm2.4956 30817 4934 19758 407 -Prdm2.5781 7580 2678 7412 1599 -Prdm4.1943 32986 1564 27413 5021 -Prdm4.2535 5176 1 4929 841 -Prdm4.3139 3980 0 1329 3 -Prdm4.3391 12217 729 13747 1087 -Prdm4.3667 189 0 71 0 -Prdm5.908 17017 2184 16584 2824 -Prdm5.984 9047 5630 6870 1405 -Prdm5.1353 5507 11532 2450 2925 -Prdm5.2148 29180 20887 26070 15137 -Prdm6.1018 8513 95 9250 75 -Prdm6.1790 27811 2748 38933 5747 -Prdm6.1823 10397 3921 13953 3896 -Prdm6.1839 8440 2848 8331 542 -Prdm8.2290 2074 1 1661 1 -Prdm8.3042 18563 110944 22244 10919 -Prdm8.3048 9249 10791 8032 922 -Prdm8.3062 34157 8769 24864 11608 -Prdm9.77 8384 2377 9245 4796 -Prdm9.496 2638 207 1667 611 -Prdm9.1838 28476 11399 32679 6714 -Prkaa1.145 15289 2584 16946 1937 -Prkaa1.1981 7523 146 8342 164 -Prkaa1.3080 1662 0 458 0 -Prkaa1.3635 51745 221378 47732 100294 -Prkaa1.3954 3718 0 3379 89 -Prkaa1.4596 14178 836 18454 170 -Prkaa2.2299 2066 1 4279 35 -Prkaa2.2748 1877 680 1923 614 -Prkaa2.4825 0 0 21 0 -Prkaa2.6172 2701 0 2936 119 -Prkaa2.6849 21406 1548 23709 4690 -Prkcd.161 5086 508 6961 1803 -Prkcd.441 685 1 1449 947 -Prkcd.707 9014 9663 10168 2609 -Prkcd.1389 1525 978 1423 2661 -Prmt1.243 15068 1812 18422 1862 -Prmt1.264 46040 17605 55341 9030 -Prmt1.630 20371 35935 26429 23619 -Prmt1.1014 26740 17066 25371 8374 -Prmt2.151 7523 284 7173 183 -Prmt2.154 8667 10496 12546 9225 -Prmt2.1066 5444 1 4843 0 -Prmt2.1067 11455 7496 10344 10105 -Prmt3.502 2673 842 4409 0 -Prmt3.814 7852 0 10218 1 -Prmt3.838 26818 112940 29743 86471 -Prmt3.985 43276 18317 37898 4768 -Prmt3.1839 2270 338 6325 498 -Prmt5.56 1674 759 613 677 -Prmt5.266 40637 7070 40157 9218 -Prmt5.2152 5093 390 7676 1360 -Prmt5.2293 8377 3933 8176 31947 -Prmt6.247 16408 14 12340 822 -Prmt6.1493 4884 1134 4611 168 -Prmt6.1983 10376 1738 7729 1099 -Prmt6.2355 7539 4086 9278 4263 -Prmt7.23 1245 6 1139 16 -Prmt7.45 41811 21691 44665 25418 -Prmt7.88 21561 1050 22146 2492 -Prmt7.1284 11267 1422 12595 48 -Prmt7.2135 13417 5187 13065 1089 -Prmt8.302 32365 6417 32121 9345 -Prmt8.455 29562 23733 30364 11859 -Prmt8.667 9965 870 10199 41 -Prmt8.1854 35676 2488 32704 4795 -Psip1.763 4282 0 4395 73 -Psip1.1311 2929 0 7223 0 -Psip1.1596 24286 2117 24019 775 -Psip1.2474 10661 133 13615 0 -Psip1.2652 54657 5848 56080 947 -Rbbp4.2088 14907 1879 17367 4542 -Rbbp4.2174 2162 0 1290 15 -Rbbp4.2511 23749 23858 32454 27646 -Rbbp4.3753 8597 1167 6013 66 -Rbbp5.1634 33001 38166 28644 25077 -Rbbp5.2248 29504 43 32701 4 -Rbbp5.2655 6168 1052 11246 825 -Rbbp5.2974 7237 10464 10292 13922 -Renilla.713 367178 563164 344553 620131 -Ring1.260 1691 45 1582 863 -Ring1.669 11819 2018 8157 1301 -Ring1.1034 4600 75 7179 2477 -Rnf2.1856 7494 6249 13866 7112 -Rnf2.2203 30535 25972 25569 27068 -Rnf2.2538 46115 24976 46018 52199 -Rnf2.2809 9879 810 8811 2579 -Rnf2.2875 37646 26066 40057 16086 -Rnf20.420 36503 1984 34359 2525 -Rnf20.948 33597 14226 54979 7373 -Rnf20.1295 4427 0 4587 1 -Rnf20.3244 0 0 0 0 -Rnf20.3277 41281 33163 38179 4449 -Rnf20.3718 12555 17757 8721 7494 -Rpa1.1620 45458 16 57357 807 -Rpa3.276 35854 4 28720 1 -Rpa3.455 66725 1381 54371 851 -Rpa3.561 208162 536 199970 1389 -Satb1.710 5263 1702 7524 4 -Satb1.1401 36326 12944 26886 11529 -Satb1.1478 4562 2161 5968 38 -Satb1.1709 14269 1071 12405 3873 -Satb1.2566 3710 131 1155 407 -Setd1a.119 4384 748 4155 184 -Setd1a.388 33695 22014 30190 17010 -Setd1a.643 38998 65977 44426 60023 -Setd1a.5859 12239 11023 14509 10084 -Setd1b.3553 11381 0 18226 3 -Setd1b.3557 10915 1966 9020 1635 -Setd1b.4520 20976 1076 17850 6222 -Setd1b.4522 5428 0 10172 68 -Setd1b.4699 29600 2899 29677 5249 -Setd2.182 50766 2411 51817 1703 -Setd2.1467 7627 0 8664 3 -Setd2.1785 19426 534 23462 1152 -Setd2.3632 15881 7077 15278 4722 -Setd2.4051 8105 0 9809 0 -Setd3.795 3477 95 4288 970 -Setd3.1496 424 0 150 0 -Setd3.2395 5170 0 7159 175 -Setd4.506 8915 16 7889 13 -Setd4.1308 19600 1 30802 0 -Setd4.1517 2249 0 1736 0 -Setd7.4328 27912 38276 31452 6959 -Setd7.5317 23119 13552 19804 5863 -Setd7.5342 29195 1276 25869 6316 -Setd7.5940 0 0 0 0 -Setd7.7009 40400 1995 34707 2878 -Setd8.2578 4113 4 3366 1274 -Setd8.2622 42611 26560 45421 9076 -Setd8.2632 86958 216794 99707 79091 -Setdb1.1145 22800 10730 18391 10380 -Setdb1.1925 19087 0 12578 2178 -Setdb1.2174 9258 1 6981 2039 -Setdb1.3684 11551 1 13226 274 -Setdb2.809 10440 29022 8305 21 -Setdb2.810 37568 36190 41634 58990 -Setdb2.990 28467 613 24673 3385 -Setdb2.1417 9056 3565 14238 4287 -Setmar.1193 18271 6544 15427 3510 -Setmar.1195 9944 1350 9967 1878 -Setmar.1589 23950 1248927 26938 2049408 -Sfmbt1.868 7566 9131 8793 7208 -Sfmbt1.1345 9354 98 8211 55 -Sfmbt1.1802 3435 2478 2641 3402 -Sfmbt1.2018 2922 1389 1521 90 -Sfmbt1.2421 14771 24 12907 1929 -Sfmbt2.602 14404 7493 12974 547 -Sfmbt2.3592 7795 44 3204 513 -Sfmbt2.5673 10825 213 8582 2138 -Sin3a.531 634 0 1702 0 -Sin3a.3537 22343 0 23130 1126 -Sin3a.3559 3950 11186 4588 2872 -Sin3a.4729 2903 0 3390 0 -Sin3b.188 6644 562 7276 0 -Sin3b.326 40114 91267 52170 31420 -Sin3b.338 6940 0 4025 850 -Sin3b.381 3401 844 1798 39 -Sin3b.475 4577 5120 5887 945 -Sirt1.688 19362 38333 23363 21555 -Sirt1.1708 197153 144560 193622 102444 -Sirt1.1779 17885 6024 15615 8384 -Sirt1.2191 7851 19851 6431 5987 -Sirt2.735 10121 31 8695 2542 -Sirt2.1418 51603 4818 41566 7049 -Sirt2.1460 9317 2705 4885 1287 -Sirt2.1600 28368 738 27560 591 -Sirt3.462 12608 8937 23079 3496 -Sirt3.869 7400 241 6738 958 -Sirt3.993 8931 9252 7877 9460 -Sirt3.1002 2040 426 2568 1087 -Sirt3.1236 15566 3873 20108 4350 -Sirt4.105 28968 24512 24897 18143 -Sirt4.633 14159 257 11725 9490 -Sirt4.1490 7280 3400 12576 961 -Sirt4.1806 21710 7905 25165 1464 -Sirt5.586 41392 2529 43804 1104 -Sirt5.1032 981 0 444 671 -Sirt5.1219 43332 63257 35460 30451 -Sirt5.1290 14394 2383 24051 3183 -Sirt6.83 24755 1313 21310 405 -Sirt6.421 14293 0 12196 3 -Sirt6.937 17858 2868 28828 8748 -Sirt6.1609 18792 1621 18577 11944 -Sirt7.841 2362 0 2342 0 -Sirt7.844 30249 3373 28104 9318 -Sirt7.1238 14603 3027 8531 1909 -Sirt7.1604 3339 13 3293 767 -Sirt7.1677 8411 4502 6020 2215 -Smarca1.1401 33840 57146 25759 15929 -Smarca1.1430 29317 23044 26964 3632 -Smarca1.1613 26153 1619 25359 4043 -Smarca1.1893 15155 3318 11343 2367 -Smarca1.3418 18683 20393 21196 2633 -Smarca2.263 28313 5055 19538 3254 -Smarca2.274 799 0 685 0 -Smarca2.712 3352 13 4803 323 -Smarca2.1061 18983 2278 7875 323 -Smarca4.3232 1287 0 1543 0 -Smarca4.3364 12192 0 9172 3410 -Smarca4.3633 12283 2082 7827 268 -Smarca4.4935 20721 13230 19425 5625 -Smarca4.5466 2050 0 1324 0 -Smarca5.1139 38415 1132532 46081 2237665 -Smarca5.1264 11896 1222 13262 0 -Smarca5.3886 10888 46556 5016 7539 -Smarca5.4421 1718 81 4763 33 -Smarca5.4522 10483 13647 10095 20371 -Smarcc2.1398 29247 234724 29717 98347 -Smarcc2.1941 4410 553 7885 9608 -Smarcc2.2235 15214 6310 16647 2339 -Smarcc2.2541 15431 6136 13795 4700 -Smarcd1.690 13166 129 15195 758 -Smarcd1.986 14993 3694 16328 724 -Smarcd1.1738 8832 11477 8520 1934 -Smarcd1.1858 10888 3275 9600 888 -Smarcd3.518 12413 2339 11321 342 -Smarcd3.847 26274 4645 19349 7316 -Smarcd3.1323 28661 13110 28557 6669 -Smarcd3.1591 4047 935 3632 15 -Smarcd3.1708 2642 0 8094 0 -Smarce1.2096 9533 1983 6689 1627 -Smarce1.2121 36774 145025 36347 291079 -Smarce1.2154 29474 1127 40937 12039 -Smarce1.2337 28357 12960 30056 20823 -Smarce1.2593 11618 786 9889 1345 -Smyd1.1302 18136 2610 24378 2014 -Smyd1.1635 22181 16847 24576 23009 -Smyd1.1658 1744 139 1322 1184 -Smyd2.334 6201 2644 8081 1941 -Smyd2.640 4778 0 8728 0 -Smyd2.1421 5873 43 8087 485 -Smyd2.1476 29280 4886 27735 2780 -Smyd3.306 36640 64693 27190 5504 -Smyd3.438 7299 2499 7015 1359 -Smyd3.980 7252 51716 12288 65481 -Smyd3.1506 11477 0 9246 0 -Smyd3.2607 20309 10800 20516 5798 -Smyd4.693 7240 0 6185 429 -Smyd4.2959 10105 1792 11907 850 -Smyd4.3333 23476 3958 24531 9662 -Smyd4.3414 9832 633 10665 83 -Smyd4.3439 24075 2841 30616 2676 -Smyd5.1548 3233 3575 2919 14 -Smyd5.1643 22979 5462 25329 4173 -Smyd5.2044 4110 0 5406 1087 -Smyd5.2048 32582 187333 27131 88007 -Srcap.2697 2734 0 4412 3083 -Srcap.3130 26303 6435 28044 5059 -Srcap.5342 25111 1863 34202 1023 -Srcap.7360 2702 1 2989 0 -Srcap.11381 33874 12408 23101 5718 -Ssrp1.306 9024 0 5331 1396 -Ssrp1.577 11830 0 10214 0 -Ssrp1.897 1979 0 1920 0 -Ssrp1.975 9139 0 5141 1787 -Ssrp1.2237 18404 9074 12412 6693 -Supt16h.1672 19141 0 16741 0 -Supt16h.2037 3987 0 5301 0 -Supt16h.2827 2799 0 3742 1904 -Supt16h.2999 7017 13525 9120 10585 -Suv39h1.496 9760 51 9748 99 -Suv39h1.1016 11061 2285 8960 1041 -Suv39h1.1202 9865 18 9681 8563 -Suv39h1.1471 37679 28758 31264 26986 -Suv39h1.1827 8924 0 8966 26 -Suv39h2.1395 11929 19031 17833 17100 -Suv39h2.1871 14656 12220 13167 18556 -Suv39h2.2981 45343 27039 52720 14100 -Suv39h2.4184 35743 5240 31412 6431 -Suv420h1.1112 38281 18821 28569 15950 -Suv420h1.1327 3903 0 5390 1259 -Suv420h1.3263 15175 7482 15676 3830 -Suv420h1.3357 6838 14010 10166 6097 -Suv420h2.287 4714 35 1766 68 -Suv420h2.686 12691 1372 12522 1533 -Suv420h2.825 3954 0 4272 15 -Suz12.909 19186 788 22747 876 -Suz12.1676 48602 41328 42913 5210 -Suz12.1842 20807 0 26947 0 -Suz12.3979 34551 25839 37312 26473 -Suz12.4300 95918 361295 105525 82284 -Taf1.928 29566 17762 30431 7446 -Taf1.3994 3805 11349 4811 10913 -Taf1.5030 16687 97640 11553 1419722 -Taf1.7786 26447 3893 17078 15382 -Taf3.1009 47005 40334 56864 22863 -Taf3.1315 9721 1 11094 5798 -Taf3.1769 7972 348 4563 2535 -Taf3.2951 2050 0 3001 0 -Taf3.3182 2441 4367 7877 4886 -Ube2a.142 6844 0 10490 0 -Ube2a.786 26843 3732 31512 3188 -Ube2a.1206 16679 1913 13264 2325 -Ube2a.1411 12770 1093 15872 551 -Ube2b.776 11624 596 15283 991 -Ube2b.1626 5770 228 4749 460 -Ube2b.1661 11131 10339 15579 1101 -Ube2b.2075 36359 11211 35981 12669 -Ube2b.2079 27519 36285 22274 73852 -Ube2e1.228 9870 580 7343 0 -Ube2e1.858 44362 142918 47668 36510 -Ube2e1.1041 27358 51197 25570 21613 -Ube2e1.1126 7564 45 9319 711 -Ube2e1.1207 17571 12619 15690 7099 -Ube2e1.1357 64966 13745 77653 28390 -Ube2i.40 2401 1010 2600 1494 -Ube2i.2212 62796 63531 58362 90071 -Ube2i.2447 6276 607 7252 0 -Ube2i.2498 51201 35736 51072 80735 -Usp22.1429 13262 5695 17290 9139 -Usp22.2382 31385 3450 32459 3697 -Usp22.2760 8601 267 5822 541 -Usp22.3603 1065 1 273 0 -Usp27x.1408 3564 45 4275 997 -Usp27x.2829 25035 4402 24751 8224 -Usp27x.2922 2730 1290 3453 578 -Usp27x.3592 6464 341 5536 2973 -Usp27x.3593 14001 3741 11248 384504 -Usp51.737 1039 406 562 802 -Usp51.1997 53674 23257 51654 9694 -Usp51.2109 7975 1484 8900 1269 -Usp51.2114 12165 116 13434 917 -Usp51.2194 3678 724 1318 2196 -Utx.652 13068 56560 19451 96391 -Utx.888 18640 32639 23825 9547 -Utx.1445 17137 32295 23244 29207 -Utx.4317 33766 102551 27815 12107 -Utx.4510 12851 40012 12155 17742 -Wbp7.2972 24413 60018 36070 20515 -Wbp7.3029 8164 0 11414 806 -Wbp7.5587 1840 0 2933 0 -Wbp7.6965 2142 0 1208 0 -Wdr5.501 9132 40067 12091 5193 -Wdr5.502 7780 475 6238 144 -Wdr5.1321 33084 8610 29142 6825 -Wdr5.1765 15206 0 11812 0 -Wdr5.2837 10752 1577 8922 76 -Wdr82.1889 9318 158922 6926 133595 -Wdr82.3590 102793 67621 100194 42465 -Wdr82.3705 25607 2390 22211 5706 -Wdr82.4023 47467 54245 35961 10951 -Whsc1.812 5301 8373 8384 1919 -Whsc1.818 21079 7170 18333 11013 -Whsc1.3055 20202 3 16818 4080 -Whsc1.3056 14848 3566 17067 3063 -Whsc1l1.276 8983 16 15356 86 -Whsc1l1.373 24335 1 18394 19 -Whsc1l1.524 25667 33492 20530 18722 -Whsc1l1.1307 36165 3810 43502 5067 -Whsc1l1.1653 1740 0 2619 0 -Wnt5a.2013 14662 2054 14921 8784 -Wnt5a.2659 31981 25084 30296 21463 -Wnt5a.2764 3508 402 4188 0 -Wnt5a.4154 24598 41766 25258 11415 diff -r a72211e03b38 -r c1b3da0fde4a test-data/zuber-sample_anno.txt --- a/test-data/zuber-sample_anno.txt Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,5 +0,0 @@ -"ID" "group" -"Reads_A_T0" "Day 0" -"Reads_A_T14" "Day 14" -"Reads_B_T0" "Day 0" -"Reads_B_T14" "Day 14" diff -r a72211e03b38 -r c1b3da0fde4a test-data/zuber-target_anno.txt --- a/test-data/zuber-target_anno.txt Mon Jan 19 22:11:00 2015 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1106 +0,0 @@ -ID Gene GeneID Pool shRNA_start Mean_T14.T0 T14.T0_A T14.T0_B -100043305.2 100043305 100043305 LIB 158 0.200312349 0.268684264 0.131940433 -100043305.4 100043305 100043305 LIB 369 0.665480322 0.000178923 1.330781721 -100043305.5 100043305 100043305 LIB 458 0.410099904 0.199787845 0.620411962 -2900092E17Rik.377 2900092E17Rik 67278 LIB 377 0.002146138 0.00204099 0.002251286 -2900092E17Rik.546 2900092E17Rik 67278 LIB 546 0.004655918 0.008377548 0.000934288 -2900092E17Rik.1051 2900092E17Rik 67278 LIB 1051 0.273324357 0.165854931 0.380793783 -2900092E17Rik.1361 2900092E17Rik 67278 LIB 1361 0.2489911 0.201788909 0.29619329 -Actl6b.379 Actl6b 83766 LIB 379 0.449690571 0.432060881 0.467320261 -Actl6b.819 Actl6b 83766 LIB 819 0.557452935 0.742589485 0.372316384 -Actl6b.917 Actl6b 83766 LIB 917 0.001775631 0.000845309 0.002705953 -Actl6b.989 Actl6b 83766 LIB 989 0.234356062 0.322320709 0.146391415 -Actl6b.1221 Actl6b 83766 LIB 1221 0.056185902 0.070641078 0.041730727 -Alkbh2.462 Alkbh2 231642 LIB 462 0.221138799 0 0.442277597 -Alkbh2.557 Alkbh2 231642 LIB 557 0.564841845 0.680914972 0.448768717 -Alkbh2.590 Alkbh2 231642 LIB 590 NA NA NA -Alkbh2.640 Alkbh2 231642 LIB 640 0.274406089 0.334058432 0.214753745 -Alkbh2.641 Alkbh2 231642 LIB 641 0.625663102 1.012713108 0.238613096 -Alkbh3.552 Alkbh3 69113 LIB 552 0.035169734 0.012261229 0.058078239 -Alkbh3.843 Alkbh3 69113 LIB 843 0.095823083 0.006448957 0.185197208 -Alkbh3.901 Alkbh3 69113 LIB 901 0.499065664 0.927424983 0.070706346 -Alkbh3.1184 Alkbh3 69113 LIB 1184 0.705258812 0.517585507 0.892932117 -Aof2.1869 Aof2 99982 LIB 1869 0.001459856 0.000206825 0.002712886 -Aof2.1956 Aof2 99982 LIB 1956 0.088104342 0.008071553 0.168137131 -Aof2.2435 Aof2 99982 LIB 2435 0.195980329 0.234741368 0.15721929 -Aof2.2857 Aof2 99982 LIB 2857 0 0 0 -Ash1l.1031 Ash1l 192195 LIB 1031 0.31947451 0.313544189 0.32540483 -Ash1l.1280 Ash1l 192195 LIB 1280 0.167683133 0.220091783 0.115274483 -Ash1l.3810 Ash1l 192195 LIB 3810 NA NA NA -Ash1l.8132 Ash1l 192195 LIB 8132 0.401332534 0.200805702 0.601859367 -Ash1l.9540 Ash1l 192195 LIB 9540 0.139184254 0.254215372 0.024153137 -Ash2l.586 Ash2l 23808 LIB 586 0.46112578 0.22570026 0.696551301 -Ash2l.805 Ash2l 23808 LIB 805 0.573261557 0.767245885 0.37927723 -Ash2l.948 Ash2l 23808 LIB 948 0.235730162 0.418269791 0.053190532 -Ash2l.1135 Ash2l 23808 LIB 1135 0.035165394 0.002115526 0.068215262 -Ash2l.2130 Ash2l 23808 LIB 2130 1.241609259 1.460589922 1.022628597 -Asxl1.2020 Asxl1 228790 LIB 2020 0.059766771 0.009568839 0.109964703 -Asxl1.3548 Asxl1 228790 LIB 3548 0.10962211 0.118078719 0.101165501 -Asxl1.3785 Asxl1 228790 LIB 3785 0.418395785 0.701615799 0.135175771 -Asxl1.4792 Asxl1 228790 LIB 4792 0.292975143 0.202313712 0.383636573 -Asxl1.5221 Asxl1 228790 LIB 5221 NA NA NA -Asxl1.6315 Asxl1 228790 LIB 6315 0.42809245 0.550629344 0.305555556 -Asxl2.11 Asxl2 75302 LIB 11 0.069299389 0.09512504 0.043473739 -Asxl2.4563 Asxl2 75302 LIB 4563 1.831446558 1.40504451 2.257848606 -Asxl2.6593 Asxl2 75302 LIB 6593 0.590189219 1.1171875 0.063190938 -Asxl2.7130 Asxl2 75302 LIB 7130 0.366813082 0.684577114 0.049049049 -Asxl2.7253 Asxl2 75302 LIB 7253 0.117667517 0 0.235335034 -Asxl3.6101 Asxl3 211961 LIB 6101 0.375913898 0.327116212 0.424711584 -Asxl3.6824 Asxl3 211961 LIB 6824 NA NA NA -Asxl3.8947 Asxl3 211961 LIB 8947 0.296002749 0.122132318 0.469873181 -Asxl3.10021 Asxl3 211961 LIB 10021 0.026435101 0.00690583 0.045964372 -Asxl3.11070 Asxl3 211961 LIB 11070 0.049530555 0.063099738 0.035961372 -Asxl3.11073 Asxl3 211961 LIB 11073 0.027907605 0.003065917 0.052749293 -Atm.137 Atm 11920 LIB 137 6.47E-05 0.000129433 0 -Atm.4098 Atm 11920 LIB 4098 2.922281386 4.477807971 1.366754801 -Atm.4998 Atm 11920 LIB 4998 0 0 0 -Atm.5616 Atm 11920 LIB 5616 0.443498086 0.657270086 0.229726085 -Atm.7782 Atm 11920 LIB 7782 0.260352231 0.308840206 0.211864257 -Atm.9396 Atm 11920 LIB 9396 0.60032482 0.359381765 0.841267876 -Atr.1239 Atr 245000 LIB 1239 0.005067342 0 0.010134685 -Atr.3160 Atr 245000 LIB 3160 0 0 0 -Atr.4762 Atr 245000 LIB 4762 0.149038652 0.070833921 0.227243383 -Atr.6186 Atr 245000 LIB 6186 0.128457676 0.106936416 0.149978936 -Atr.7888 Atr 245000 LIB 7888 0.147861249 0.264325323 0.031397174 -Atrx.2490 Atrx 22589 LIB 2490 0.396582444 0.600036694 0.193128195 -Atrx.5490 Atrx 22589 LIB 5490 0.356515297 0.533129237 0.179901356 -Atrx.6144 Atrx 22589 LIB 6144 4.974521294 2.266989851 7.682052736 -Atrx.7173 Atrx 22589 LIB 7173 0.05387472 0.096820809 0.01092863 -Atrx.7377 Atrx 22589 LIB 7377 0.837321391 1.529071015 0.145571768 -Aurkb.520 Aurkb 20877 LIB 520 0.008388288 0.015122511 0.001654064 -Aurkb.631 Aurkb 20877 LIB 631 0.824053234 1.06458435 0.583522118 -Aurkb.917 Aurkb 20877 LIB 917 0.024491203 0.008743956 0.04023845 -Aurkb.928 Aurkb 20877 LIB 928 0.010416667 0 0.020833333 -Aurkb.1620 Aurkb 20877 LIB 1620 0 0 0 -Aurkb.1803 Aurkb 20877 LIB 1803 0.125188349 0.175752051 0.074624647 -Baz1a.2095 Baz1a 217578 LIB 2095 0.507940486 0.356679709 0.659201262 -Baz1a.2451 Baz1a 217578 LIB 2451 2.159026811 3.284734348 1.033319275 -Baz1a.4993 Baz1a 217578 LIB 4993 0.64349492 0.507178218 0.779811623 -Baz1a.5946 Baz1a 217578 LIB 5946 0.080389068 0.05529467 0.105483466 -Baz1b.801 Baz1b 22385 LIB 801 0.000639494 0.000888362 0.000390625 -Baz1b.3683 Baz1b 22385 LIB 3683 0.360095959 0.069445862 0.650746056 -Baz1b.5646 Baz1b 22385 LIB 5646 0.016297649 0.018375115 0.014220183 -Baz1b.6371 Baz1b 22385 LIB 6371 0.14306644 0 0.286132879 -Bmi1.698 Bmi1 12151 LIB 698 0.092709454 0.069620729 0.11579818 -Bmi1.895 Bmi1 12151 LIB 895 0.035594283 0.071188567 0 -Bmi1.1440 Bmi1 12151 LIB 1440 NA NA NA -Bmi1.1746 Bmi1 12151 LIB 1746 0.118689343 0.122838849 0.114539838 -Bmi1.2404 Bmi1 12151 LIB 2404 0 0 0 -Bmi1.2561 Bmi1 12151 LIB 2561 0.454904159 0.631757214 0.278051103 -Bop1.778 Bop1 12181 LIB 778 0.672354814 0.445185419 0.899524209 -Bop1.2228 Bop1 12181 LIB 2228 0.142000285 0.127547666 0.156452904 -Bop1.2403 Bop1 12181 LIB 2403 0 0 0 -Bptf.1622 Bptf 207165 LIB 1622 0.077104921 0.08259276 0.071617083 -Bptf.3234 Bptf 207165 LIB 3234 0.057370498 0.065993919 0.048747077 -Bptf.7211 Bptf 207165 LIB 7211 0.024626408 0.021392709 0.027860107 -Bptf.8224 Bptf 207165 LIB 8224 0.410946348 0.179452295 0.6424404 -Braf.3750 Braf 109880 NC 3750 0.412381245 0.44332883 0.38143366 -Braf.3826 Braf 109880 NC 3826 0.129826198 0.1681838 0.091468596 -Braf.5053 Braf 109880 NC 5053 2.34833908 2.720656406 1.976021753 -Brd1.286 Brd1 223770 LIB 286 0.094299073 0.000374953 0.188223194 -Brd1.287 Brd1 223770 LIB 287 0.480557434 0.680387664 0.280727205 -Brd1.2096 Brd1 223770 LIB 2096 0.041243445 0.031141199 0.051345691 -Brd1.4229 Brd1 223770 LIB 4229 0.013231982 0.026463964 0 -Brd2.813 Brd2 14312 LIB 813 22.77961486 42.66701779 2.892211933 -Brd2.1714 Brd2 14312 LIB 1714 0.144143286 0.249835634 0.038450937 -Brd2.3011 Brd2 14312 LIB 3011 0.028355134 0.029962547 0.02674772 -Brd2.3396 Brd2 14312 LIB 3396 NA NA NA -Brd3.187 Brd3 67382 LIB 187 3.11E-05 0 6.22E-05 -Brd3.298 Brd3 67382 LIB 298 0.056505575 0.058248337 0.054762814 -Brd3.411 Brd3 67382 LIB 411 0.756328621 1.503010235 0.009647007 -Brd3.4162 Brd3 67382 LIB 4162 0.633054482 0.738127854 0.52798111 -Brd4.523 Brd4 57261 LIB 523 0.010380898 0.004175644 0.016586151 -Brd4.552 Brd4 57261 LIB 552 0 0 0 -Brd4.632 Brd4 57261 LIB 632 0 0 0 -Brd4.1448 Brd4 57261 LIB 1448 0.135273343 0.118396988 0.152149699 -Brd4.2097 Brd4 57261 LIB 2097 0 0 0 -Carm1.892 Carm1 59035 LIB 892 0.079435576 0.000380084 0.158491069 -Carm1.1222 Carm1 59035 LIB 1222 0.075280112 0 0.150560224 -Carm1.1454 Carm1 59035 LIB 1454 0 0 0 -Carm1.1614 Carm1 59035 LIB 1614 0.243856333 0 0.487712665 -Carm1.1717 Carm1 59035 LIB 1717 0.001731885 0.002492331 0.00097144 -Cbx1.1004 Cbx1 12412 LIB 1004 0.057581903 0.083058046 0.03210576 -Cbx1.1053 Cbx1 12412 LIB 1053 1.091733912 0.589759684 1.593708139 -Cbx1.1099 Cbx1 12412 LIB 1099 0.57419689 0.919432666 0.228961114 -Cbx1.1103 Cbx1 12412 LIB 1103 0.458716872 0.142857143 0.774576601 -Cbx1.1210 Cbx1 12412 LIB 1210 0.245937138 0.37322759 0.118646686 -Cbx2.2033 Cbx2 12416 LIB 2033 0.134848542 0.001576873 0.268120212 -Cbx2.3537 Cbx2 12416 LIB 3537 0 0 0 -Cbx2.3545 Cbx2 12416 LIB 3545 0.710820484 1.275496689 0.146144279 -Cbx2.3620 Cbx2 12416 LIB 3620 0.134612189 0.008686441 0.260537937 -Cbx2.3706 Cbx2 12416 LIB 3706 1.147329284 1.49221144 0.802447127 -Cbx3.882 Cbx3 12417 LIB 882 0 0 0 -Cbx3.1206 Cbx3 12417 LIB 1206 0.118944773 0.131788129 0.106101417 -Cbx3.1339 Cbx3 12417 LIB 1339 0.142134201 0.070435009 0.213833393 -Cbx3.1719 Cbx3 12417 LIB 1719 0 0 0 -Cbx3.1735 Cbx3 12417 LIB 1735 0.115344034 0.011380552 0.219307515 -Cbx4.1794 Cbx4 12418 LIB 1794 1.364806716 0.371060327 2.358553106 -Cbx4.1844 Cbx4 12418 LIB 1844 0.700301215 1.223163842 0.177438588 -Cbx4.2573 Cbx4 12418 LIB 2573 0.817611719 0.890839629 0.744383809 -Cbx4.4403 Cbx4 12418 LIB 4403 0.215720626 0 0.431441252 -Cbx4.5120 Cbx4 12418 LIB 5120 0.497429027 0.398906637 0.595951417 -Cbx5.1309 Cbx5 12419 LIB 1309 0.986138423 0.975527017 0.996749828 -Cbx5.4366 Cbx5 12419 LIB 4366 0 0 0 -Cbx5.4409 Cbx5 12419 LIB 4409 0.18203172 0.15420805 0.20985539 -Cbx5.4508 Cbx5 12419 LIB 4508 0.693812292 0.764903255 0.622721329 -Cbx5.5707 Cbx5 12419 LIB 5707 0.232529345 0.127116437 0.337942253 -Cbx5.8586 Cbx5 12419 LIB 8586 0.176272377 0.350797267 0.001747488 -Cbx6.1535 Cbx6 494448 LIB 1535 1.317433547 0.026128266 2.608738828 -Cbx6.3332 Cbx6 494448 LIB 3332 0.628106622 1.114166972 0.142046271 -Cbx6.3473 Cbx6 494448 LIB 3473 1.362208923 0.193768257 2.530649588 -Cbx6.3969 Cbx6 494448 LIB 3969 0.591043966 0.80244028 0.379647652 -Cbx7.745 Cbx7 52609 LIB 745 0.218502726 0.203358299 0.233647153 -Cbx7.1633 Cbx7 52609 LIB 1633 0.040584859 0 0.081169719 -Cbx7.1634 Cbx7 52609 LIB 1634 0.075718892 0.000117758 0.151320026 -Cbx7.1639 Cbx7 52609 LIB 1639 0.100164464 0.124590164 0.075738763 -Cbx7.2006 Cbx7 52609 LIB 2006 0.080469517 0 0.160939034 -Cbx7.2504 Cbx7 52609 LIB 2504 0.038731085 0.004728435 0.072733736 -Cbx8.136 Cbx8 30951 LIB 136 0.110253195 0.038949338 0.181557052 -Cbx8.1120 Cbx8 30951 LIB 1120 0.226325463 0.218088273 0.234562653 -Cbx8.1342 Cbx8 30951 LIB 1342 1.082538396 1.289585162 0.87549163 -Chaf1a.166 Chaf1a 27221 LIB 166 0 0 0 -Chaf1a.1039 Chaf1a 27221 LIB 1039 0 0 0 -Chaf1a.2122 Chaf1a 27221 LIB 2122 0.397909545 0.698496344 0.097322746 -Chaf1b.367 Chaf1b 110749 LIB 367 0 0 0 -Chaf1b.566 Chaf1b 110749 LIB 566 0.303408945 0.482990787 0.123827104 -Chaf1b.692 Chaf1b 110749 LIB 692 0.287092522 0.574185043 0 -Chaf1b.901 Chaf1b 110749 LIB 901 0.20895781 0.141891892 0.276023728 -Chaf1b.1223 Chaf1b 110749 LIB 1223 0.040480317 0 0.080960634 -Chd1.746 Chd1 12648 LIB 746 0.109569072 0.112458184 0.10667996 -Chd1.1103 Chd1 12648 LIB 1103 0.03061677 0.03155467 0.029678869 -Chd1.2443 Chd1 12648 LIB 2443 0.119970268 0.110483782 0.129456754 -Chd1.2959 Chd1 12648 LIB 2959 0.204016851 0.209087277 0.198946425 -Chd1.4558 Chd1 12648 LIB 4558 0.579893278 1.122087605 0.037698952 -Chd1l.2305 Chd1l 68058 LIB 2305 0.171659277 0.161353286 0.181965268 -Chd1l.2598 Chd1l 68058 LIB 2598 0.064918568 0.001997004 0.127840131 -Chd1l.2804 Chd1l 68058 LIB 2804 0.320682295 0.225751283 0.415613308 -Chd2.926 Chd2 244059 LIB 926 0.138050187 0.180178767 0.095921607 -Chd2.3700 Chd2 244059 LIB 3700 0.397415785 0.434250439 0.360581131 -Chd2.3984 Chd2 244059 LIB 3984 0.134215951 0.080257186 0.188174716 -Chd2.8087 Chd2 244059 LIB 8087 0.189600975 0.263537572 0.115664379 -Chd2.8913 Chd2 244059 LIB 8913 0.073920542 0.106108526 0.041732558 -Chd3.482 Chd3 216848 LIB 482 0.08107178 0.014856739 0.147286822 -Chd3.3249 Chd3 216848 LIB 3249 0.071321859 0.011487304 0.131156413 -Chd3.4011 Chd3 216848 LIB 4011 0.289503582 0.42626498 0.152742183 -Chd3.6496 Chd3 216848 LIB 6496 0.044090494 0.030532487 0.057648502 -Chd3.7148 Chd3 216848 LIB 7148 2.340233512 1.930658742 2.749808282 -Chd3.7149 Chd3 216848 LIB 7149 0.156093321 0.116246872 0.19593977 -Chd4.2060 Chd4 107932 LIB 2060 0.000158747 0 0.000317494 -Chd4.3326 Chd4 107932 LIB 3326 NA NA NA -Chd4.3423 Chd4 107932 LIB 3423 0.039003519 0.018129718 0.059877321 -Chd4.3772 Chd4 107932 LIB 3772 0.446854315 0.107456979 0.786251651 -Chd5.2301 Chd5 269610 LIB 2301 0.890171552 1.716215543 0.064127562 -Chd5.2900 Chd5 269610 LIB 2900 2.179569236 1.422986617 2.936151855 -Chd5.5471 Chd5 269610 LIB 5471 0.031951327 0.008029979 0.055872675 -Chd5.6392 Chd5 269610 LIB 6392 1.431979693 1.532967033 1.330992354 -Chd6.311 Chd6 71389 LIB 311 0.034464804 0.005788154 0.063141455 -Chd6.4698 Chd6 71389 LIB 4698 0.079293047 0.058312236 0.100273857 -Chd6.4988 Chd6 71389 LIB 4988 0.706143751 0.96534451 0.446942993 -Chd6.9610 Chd6 71389 LIB 9610 0.621464656 0.915195867 0.327733445 -Chd7.1269 Chd7 320790 LIB 1269 4.781464099 6.785229842 2.777698356 -Chd7.1502 Chd7 320790 LIB 1502 0.778617907 1.132855191 0.424380624 -Chd7.5857 Chd7 320790 LIB 5857 1.176684021 1.753802163 0.599565878 -Chd7.6498 Chd7 320790 LIB 6498 0.554422725 0.923791103 0.185054348 -Chd7.7229 Chd7 320790 LIB 7229 1.1593543 0.786077021 1.532631579 -Chd8.434 Chd8 67772 LIB 434 0.240881821 0.481763642 0 -Chd8.3265 Chd8 67772 LIB 3265 2.777624937 3.217093529 2.338156344 -Chd8.4169 Chd8 67772 LIB 4169 2.352884012 2.797262325 1.908505699 -Chd8.5352 Chd8 67772 LIB 5352 0.046980193 0 0.093960386 -Chd8.6946 Chd8 67772 LIB 6946 0.082319013 0.141659648 0.022978377 -Chd9.1402 Chd9 109151 LIB 1402 2.015703082 1.209699299 2.821706865 -Chd9.3919 Chd9 109151 LIB 3919 0.232392142 0.178955954 0.285828331 -Chd9.9352 Chd9 109151 LIB 9352 0.063600987 0.001541511 0.125660464 -Chd9.10928 Chd9 109151 LIB 10928 0.281642373 0.071780078 0.491504669 -Clock.693 Clock 12753 LIB 693 4.165656967 6.332554466 1.998759467 -Clock.1387 Clock 12753 LIB 1387 0.154177662 0.004555809 0.303799515 -Clock.4461 Clock 12753 LIB 4461 2.081932577 1.782110872 2.381754283 -Clock.4611 Clock 12753 LIB 4611 0.186897319 0.248041429 0.125753209 -Clock.5863 Clock 12753 LIB 5863 0 0 0 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0.199257294 -Dmap1.439 Dmap1 66233 LIB 439 0.703875338 0.77262223 0.635128445 -Dmap1.518 Dmap1 66233 LIB 518 NA NA NA -Dmap1.1354 Dmap1 66233 LIB 1354 0.14763293 0.098111837 0.197154022 -Dmap1.1355 Dmap1 66233 LIB 1355 0.42757955 0.089182969 0.765976131 -Dmap1.1487 Dmap1 66233 LIB 1487 1.398029255 2.142666181 0.65339233 -Dnmt1.437 Dnmt1 13433 LIB 437 0.216593143 0.00036049 0.432825795 -Dnmt1.828 Dnmt1 13433 LIB 828 0.031108522 0 0.062217045 -Dnmt1.1137 Dnmt1 13433 LIB 1137 0 0 0 -Dnmt1.4462 Dnmt1 13433 LIB 4462 0.107595678 0.084457173 0.130734182 -Dnmt1.4848 Dnmt1 13433 LIB 4848 2.73965767 4.554970263 0.924345077 -Dnmt3a.16 Dnmt3a 13435 LIB 16 1.725217186 1.842114421 1.608319951 -Dnmt3a.1669 Dnmt3a 13435 LIB 1669 0.151960261 0.274109644 0.029810877 -Dnmt3a.2338 Dnmt3a 13435 LIB 2338 0.464228303 0.546660024 0.381796582 -Dnmt3a.4173 Dnmt3a 13435 LIB 4173 2.839755061 1.630561738 4.048948383 -Dnmt3b.275 Dnmt3b 13436 LIB 275 0.111149425 0 0.222298851 -Dnmt3b.579 Dnmt3b 13436 LIB 579 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433759 LIB 245 0.23785439 0.369592346 0.106116433 -Hdac1.1053 Hdac1 433759 LIB 1053 0.441444289 0.704354469 0.17853411 -Hdac1.1065 Hdac1 433759 LIB 1065 0.003350221 0.006700441 0 -Hdac1.1830 Hdac1 433759 LIB 1830 1.267186229 0.331748957 2.2026235 -Hdac10.1645 Hdac10 170787 LIB 1645 NA NA NA -Hdac10.2041 Hdac10 170787 LIB 2041 0.034962353 0.003184375 0.066740331 -Hdac10.2307 Hdac10 170787 LIB 2307 0.244272107 0.406371338 0.082172877 -Hdac11.2025 Hdac11 232232 LIB 2025 0.034038791 0.067849687 0.000227894 -Hdac11.2058 Hdac11 232232 LIB 2058 0.616567512 0.530961372 0.702173652 -Hdac11.2182 Hdac11 232232 LIB 2182 0 0 0 -Hdac11.2460 Hdac11 232232 LIB 2460 0.179395578 0.071746032 0.287045124 -Hdac11.2461 Hdac11 232232 LIB 2461 0.106169791 0.145963878 0.066375705 -Hdac2.439 Hdac2 15182 LIB 439 0.120428617 0.098365041 0.142492194 -Hdac2.440 Hdac2 15182 LIB 440 0 0 0 -Hdac2.1184 Hdac2 15182 LIB 1184 1.736519405 1.729724166 1.743314643 -Hdac2.1611 Hdac2 15182 LIB 1611 0.555755616 0.901804888 0.209706344 -Hdac2.1919 Hdac2 15182 LIB 1919 0.22681503 0.273884154 0.179745907 -Hdac3.161 Hdac3 15183 LIB 161 0.027585567 0.052225083 0.00294605 -Hdac3.854 Hdac3 15183 LIB 854 0.19703596 0.313846421 0.080225499 -Hdac3.987 Hdac3 15183 LIB 987 9.200089463 15.16698706 3.23319187 -Hdac3.1037 Hdac3 15183 LIB 1037 0.194075242 0.388150484 0 -Hdac3.1491 Hdac3 15183 LIB 1491 0.078428253 0 0.156856507 -Hdac4.331 Hdac4 208727 LIB 331 0.249392869 0.421878803 0.076906935 -Hdac4.431 Hdac4 208727 LIB 431 12.91595763 23.42054693 2.41136833 -Hdac4.1903 Hdac4 208727 LIB 1903 0.656722465 0.484156227 0.829288703 -Hdac4.3273 Hdac4 208727 LIB 3273 0.086063916 0.063287745 0.108840087 -Hdac5.1115 Hdac5 15184 LIB 1115 0.146091516 0.292183031 0 -Hdac5.1936 Hdac5 15184 LIB 1936 0.311596614 0.41754442 0.205648809 -Hdac5.2060 Hdac5 15184 LIB 2060 0.050833282 0.001168224 0.100498339 -Hdac5.2412 Hdac5 15184 LIB 2412 0.153710614 7.29E-05 0.307348299 -Hdac5.2886 Hdac5 15184 LIB 2886 0.023975817 0.024090462 0.023861171 -Hdac6.530 Hdac6 15185 LIB 530 NA NA NA -Hdac6.2249 Hdac6 15185 LIB 2249 0.395188053 0.790376106 0 -Hdac6.3838 Hdac6 15185 LIB 3838 0.463447784 0.373127484 0.553768085 -Hdac6.4026 Hdac6 15185 LIB 4026 0.673906334 0.58012685 0.767685818 -Hdac7.560 Hdac7 56233 LIB 560 0.05 0.1 0 -Hdac7.836 Hdac7 56233 LIB 836 1.003143594 0.60732691 1.398960277 -Hdac7.1293 Hdac7 56233 LIB 1293 0.232796973 0.260955434 0.204638512 -Hdac7.2255 Hdac7 56233 LIB 2255 0.180458299 0.321948649 0.038967948 -Hdac7.3429 Hdac7 56233 LIB 3429 0.108629839 0.07593243 0.141327247 -Hdac8.296 Hdac8 70315 LIB 296 0 0 0 -Hdac8.397 Hdac8 70315 LIB 397 0.346191954 0.376371183 0.316012725 -Hdac8.900 Hdac8 70315 LIB 900 0.06905 0.066867307 0.071232693 -Hdac8.1692 Hdac8 70315 LIB 1692 0.716122809 0.945390961 0.486854657 -Hdac9.1236 Hdac9 79221 LIB 1236 0.061659427 0.057717972 0.065600882 -Hdac9.1449 Hdac9 79221 LIB 1449 0.043527072 0.053540314 0.03351383 -Hdac9.2031 Hdac9 79221 LIB 2031 0.20955986 0.268333519 0.1507862 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0.001332149 0.051552926 -Ing2.1400 Ing2 69260 LIB 1400 0.441872864 0.485687809 0.398057919 -Ing2.1788 Ing2 69260 LIB 1788 0.00514048 0.009192066 0.001088893 -Ing2.1824 Ing2 69260 LIB 1824 0.230878224 0.327220173 0.134536275 -Ing2.2176 Ing2 69260 LIB 2176 0.110401249 0.03625 0.184552498 -Ino80.458 Ino80 68142 LIB 458 1.017141522 0.572352773 1.461930271 -Ino80.1194 Ino80 68142 LIB 1194 0.864776346 0.582272727 1.147279965 -Ino80.2062 Ino80 68142 LIB 2062 3.479477858 2.83947293 4.119482786 -Ino80.4069 Ino80 68142 LIB 4069 4.925644667 4.280960907 5.570328426 -Jarid1a.2826 Jarid1a 214899 LIB 2826 0.248654315 0.35031185 0.14699678 -Jarid1a.6729 Jarid1a 214899 LIB 6729 1.363948366 0.535007243 2.192889488 -Jarid1a.10299 Jarid1a 214899 LIB 10299 0.263122123 0.241511541 0.284732705 -Jarid1a.10802 Jarid1a 214899 LIB 10802 0.106583794 0 0.213167587 -Jarid1a.11640 Jarid1a 214899 LIB 11640 0.311471985 0.488261591 0.134682379 -Jarid1b.382 Jarid1b 75605 LIB 382 0.18904701 0.27594244 0.10215158 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0.162322666 0.439033504 -Jmjd1c.3196 Jmjd1c 108829 LIB 3196 0.000842912 0.001685824 0 -Jmjd1c.4221 Jmjd1c 108829 LIB 4221 0.103679501 0.106351828 0.101007173 -Jmjd1c.6050 Jmjd1c 108829 LIB 6050 0.726982674 0.553239773 0.900725575 -Jmjd1c.6346 Jmjd1c 108829 LIB 6346 0.230741091 0.167158309 0.294323873 -Jmjd2a.424 Jmjd2a 230674 LIB 424 0.207264965 0.120808561 0.293721369 -Jmjd2a.663 Jmjd2a 230674 LIB 663 0.113322058 0.075793595 0.15085052 -Jmjd2a.1474 Jmjd2a 230674 LIB 1474 0.08913639 0.002784366 0.175488414 -Jmjd2a.1498 Jmjd2a 230674 LIB 1498 0.043079662 0.069152399 0.017006925 -Jmjd2a.3033 Jmjd2a 230674 LIB 3033 0.000831282 0.001034029 0.000628536 -Jmjd2b.1151 Jmjd2b 193796 LIB 1151 0.933461944 1.175144551 0.691779336 -Jmjd2b.2905 Jmjd2b 193796 LIB 2905 1.786480339 2.379093311 1.193867366 -Jmjd2b.4018 Jmjd2b 193796 LIB 4018 1.348195558 1.050841453 1.645549663 -Jmjd2b.4170 Jmjd2b 193796 LIB 4170 0.895988133 0.355499082 1.436477183 -Jmjd2c.738 Jmjd2c 76804 LIB 738 0.187741857 0.120085677 0.255398037 -Jmjd2c.1217 Jmjd2c 76804 LIB 1217 1.318076072 0.96347543 1.672676713 -Jmjd2c.3112 Jmjd2c 76804 LIB 3112 0.412965767 0.468026197 0.357905337 -Jmjd2c.3541 Jmjd2c 76804 LIB 3541 0.480747339 0.556819876 0.404674802 -Jmjd2d.301 Jmjd2d 244694 LIB 301 0.129064364 0.000328623 0.257800106 -Jmjd2d.450 Jmjd2d 244694 LIB 450 1.353922306 0.000965251 2.706879362 -Jmjd2d.1143 Jmjd2d 244694 LIB 1143 0.490140075 0.956008305 0.024271845 -Jmjd2d.2310 Jmjd2d 244694 LIB 2310 0.164979808 0.256726348 0.073233268 -Jmjd2d.2358 Jmjd2d 244694 LIB 2358 0.059442746 0.07510305 0.043782442 -Jmjd4.1722 Jmjd4 194952 LIB 1722 0.741528975 0.765657556 0.717400394 -Jmjd4.1796 Jmjd4 194952 LIB 1796 0.200102959 0.163622609 0.23658331 -Jmjd4.2677 Jmjd4 194952 LIB 2677 0.676849819 0.820704579 0.532995059 -Jmjd4.2749 Jmjd4 194952 LIB 2749 0.15829753 0.038494735 0.278100325 -Jmjd4.3327 Jmjd4 194952 LIB 3327 0.553203122 0.185103308 0.921302937 -Jmjd5.18 Jmjd5 77035 LIB 18 2.587739528 3.744000541 1.431478516 -Jmjd5.1123 Jmjd5 77035 LIB 1123 0.148414474 0.037384899 0.259444048 -Jmjd5.1291 Jmjd5 77035 LIB 1291 0.401904979 0.407221471 0.396588486 -Jmjd5.1564 Jmjd5 77035 LIB 1564 0.186949478 0.022460197 0.351438759 -Jmjd5.2041 Jmjd5 77035 LIB 2041 0.008618272 0.016029948 0.001206596 -Jmjd6.254 Jmjd6 107817 LIB 254 0.12362466 0.184941628 0.062307692 -Jmjd6.530 Jmjd6 107817 LIB 530 0.147628799 0.026531729 0.268725869 -Jmjd6.956 Jmjd6 107817 LIB 956 0.132745115 0.260845889 0.004644341 -Jmjd6.1633 Jmjd6 107817 LIB 1633 0.240665022 0.253816286 0.227513757 -Kat2a.542 Kat2a 14534 LIB 542 0.618565777 0.940924658 0.296206897 -Kat2a.1771 Kat2a 14534 LIB 1771 0.120971403 0 0.241942805 -Kat2a.2053 Kat2a 14534 LIB 2053 0.538437996 0.10757034 0.969305652 -Kat2a.2201 Kat2a 14534 LIB 2201 0.142403868 0.257946389 0.026861346 -Kat2b.1306 Kat2b 18519 LIB 1306 0.040373807 0.071984908 0.008762706 -Kat2b.2624 Kat2b 18519 LIB 2624 0.079970208 0.073811384 0.086129032 -Kat2b.3228 Kat2b 18519 LIB 3228 0.069588311 0.063063063 0.076113558 -Kat2b.3494 Kat2b 18519 LIB 3494 0.369201025 0.457417016 0.280985033 -Kat2b.3766 Kat2b 18519 LIB 3766 0.111142996 0.145979608 0.076306385 -Kat5.679 Kat5 81601 LIB 679 0.117228687 0.230010953 0.004446421 -Kat5.1193 Kat5 81601 LIB 1193 2.307918926 2.68596882 1.929869033 -Kat5.1242 Kat5 81601 LIB 1242 NA NA NA -Kat5.1387 Kat5 81601 LIB 1387 3.821357363 3.433995327 4.208719399 -L3mbtl.263 L3mbtl 241764 LIB 263 0.199214313 0.000694806 0.39773382 -L3mbtl.373 L3mbtl 241764 LIB 373 0.290562147 0.414519609 0.166604686 -L3mbtl.725 L3mbtl 241764 LIB 725 0.389300951 0.33340748 0.445194422 -L3mbtl.1906 L3mbtl 241764 LIB 1906 0.01201515 0.024030299 0 -L3mbtl.2689 L3mbtl 241764 LIB 2689 0.068187318 0.136374637 0 -LOC100040412.49 LOC100040412 100040412 LIB 49 0.235139043 0.216814556 0.253463531 -LOC100040412.495 LOC100040412 100040412 LIB 495 NA NA NA -LOC100040412.655 LOC100040412 100040412 LIB 655 0.385744528 0.194355059 0.577133998 -LOC100040412.1128 LOC100040412 100040412 LIB 1128 0.321175793 0.350280264 0.292071322 -LOC100044324.736 LOC100044324 100044324 LIB 736 0.541107405 0.527171897 0.555042912 -LOC100044324.927 LOC100044324 100044324 LIB 927 0.174749605 0.349499209 0 -LOC100044324.1075 LOC100044324 100044324 LIB 1075 4.38507001 5.72404439 3.046095631 -LOC100044324.1240 LOC100044324 100044324 LIB 1240 0.248179872 0 0.496359743 -LOC100044324.1314 LOC100044324 100044324 LIB 1314 0.215962555 0.146174702 0.285750408 -LOC100048887.186 LOC100048887 100048887 LIB 186 4.761125427 3.672516129 5.849734725 -LOC100048887.194 LOC100048887 100048887 LIB 194 0 0 0 -LOC100048887.732 LOC100048887 100048887 LIB 732 0.074897582 0.110762101 0.039033064 -LOC100048887.787 LOC100048887 100048887 LIB 787 0 0 0 -LOC100048887.803 LOC100048887 100048887 LIB 803 0.116716316 0.079717133 0.153715499 -LOC664892.1494 LOC664892 664892 LIB 1494 0.568467589 0.647703684 0.489231493 -LOC664892.1500 LOC664892 664892 LIB 1500 0.82744825 1.141203528 0.513692971 -LOC664892.1697 LOC664892 664892 LIB 1697 0.363859691 0.15822698 0.569492403 -LOC664892.1892 LOC664892 664892 LIB 1892 0.09125886 0.026162019 0.156355701 -LOC664892.2169 LOC664892 664892 LIB 2169 0.011900813 0.022360704 0.001440922 -Mbd1.746 Mbd1 17190 LIB 746 0.194643294 0.000376081 0.388910506 -Mbd1.1387 Mbd1 17190 LIB 1387 0.200901765 0.042339934 0.359463595 -Mbd1.1856 Mbd1 17190 LIB 1856 0.078750031 0.010875476 0.146624585 -Mbd1.2237 Mbd1 17190 LIB 2237 0.145222056 0.013529275 0.276914837 -Mbd2.938 Mbd2 17191 LIB 938 0.033554608 0 0.067109216 -Mbd2.1117 Mbd2 17191 LIB 1117 0.276620876 0.447187977 0.106053776 -Mbd2.1545 Mbd2 17191 LIB 1545 0.103798129 0.202524797 0.005071462 -Mbd2.1763 Mbd2 17191 LIB 1763 0.028187951 0.001406376 0.054969526 -Mbd2.1823 Mbd2 17191 LIB 1823 0.414679837 0.282276488 0.547083186 -Mbd3.579 Mbd3 17192 LIB 579 0.039006515 0.011331445 0.066681584 -Mbd3.1147 Mbd3 17192 LIB 1147 0.132003104 0.132045515 0.131960693 -Mbd3.1354 Mbd3 17192 LIB 1354 0.036617996 0.036774807 0.036461185 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0.142586776 -Mll1.13303 Mll1 214162 LIB 13303 NA NA NA -Mll1.16168 Mll1 214162 LIB 16168 0.101967298 0.1481428 0.055791796 -Mll2.4285 Mll2 381022 LIB 4285 2.378116941 2.670245399 2.085988484 -Mll2.5430 Mll2 381022 LIB 5430 0.42815757 0.457258743 0.399056397 -Mll2.6153 Mll2 381022 LIB 6153 4.914842828 4.14081359 5.688872067 -Mll2.11374 Mll2 381022 LIB 11374 15.43389955 22.53070605 8.337093044 -Mll2.12943 Mll2 381022 LIB 12943 7.90198211 4.957801222 10.846163 -Mll3.1099 Mll3 231051 LIB 1099 2.088422368 3.689806678 0.487038058 -Mll3.2993 Mll3 231051 LIB 2993 0.681144071 0.610359065 0.751929076 -Mll3.5304 Mll3 231051 LIB 5304 0 0 0 -Mll3.6232 Mll3 231051 LIB 6232 1.804491278 2.920727522 0.688255034 -Mll3.15396 Mll3 231051 LIB 15396 5.053664383 7.673024929 2.434303837 -Morf4l1.281 Morf4l1 21761 LIB 281 0.139995763 0.248305961 0.031685564 -Morf4l1.603 Morf4l1 21761 LIB 603 0.031392948 0.042246873 0.020539024 -Morf4l1.639 Morf4l1 21761 LIB 639 0.11593131 0.140696498 0.091166122 -Morf4l1.1034 Morf4l1 21761 LIB 1034 0.008070115 0.005876667 0.010263563 -Morf4l1.1245 Morf4l1 21761 LIB 1245 0.355326987 0.511142363 0.199511612 -Mta1.213 Mta1 116870 LIB 213 0 0 0 -Mta1.1003 Mta1 116870 LIB 1003 0.371959696 0.15191828 0.592001111 -Mta1.1053 Mta1 116870 LIB 1053 0.101226426 0.097185681 0.10526717 -Mta1.1147 Mta1 116870 LIB 1147 0.884542293 0.609151329 1.159933256 -Mta1.1363 Mta1 116870 LIB 1363 NA NA NA -Mta2.511 Mta2 23942 LIB 511 0.027716689 0.003469469 0.05196391 -Mta2.924 Mta2 23942 LIB 924 0.015603346 0.021342134 0.009864558 -Mta2.1284 Mta2 23942 LIB 1284 0.263205121 0.432928311 0.093481932 -Mta2.2013 Mta2 23942 LIB 2013 NA NA NA -Mta3.222 Mta3 116871 LIB 222 0 0 0 -Mta3.553 Mta3 116871 LIB 553 0.065665497 0.003378664 0.127952329 -Mta3.1523 Mta3 116871 LIB 1523 0.610472449 0.857285113 0.363659784 -Mta3.1663 Mta3 116871 LIB 1663 0.067934747 0.118514248 0.017355245 -Myst1.643 Myst1 67773 LIB 643 0 0 0 -Myst1.724 Myst1 67773 LIB 724 0.379083512 0.089139878 0.669027146 -Myst1.1250 Myst1 67773 LIB 1250 0 0 0 -Myst1.1302 Myst1 67773 LIB 1302 0.125921699 0.044815645 0.207027753 -Myst2.176 Myst2 217127 LIB 176 0.973337724 1.441661409 0.505014039 -Myst2.507 Myst2 217127 LIB 507 2.531753597 2.010045335 3.053461859 -Myst2.1183 Myst2 217127 LIB 1183 0.93839873 1.308311364 0.568486097 -Myst2.3099 Myst2 217127 LIB 3099 0.192553734 0.281569343 0.103538124 -Myst3.2590 Myst3 244349 LIB 2590 0 0 0 -Myst3.3127 Myst3 244349 LIB 3127 0 0 0 -Myst3.3485 Myst3 244349 LIB 3485 0.006118881 0.012237762 0 -Myst3.4554 Myst3 244349 LIB 4554 0.999844656 0.815379706 1.184309605 -Myst3.6844 Myst3 244349 LIB 6844 0.756310595 0.374601925 1.138019266 -Myst4.3568 Myst4 54169 LIB 3568 0.170742331 0.244378552 0.097106109 -Myst4.5452 Myst4 54169 LIB 5452 1.060119091 1.491440019 0.628798162 -Myst4.6527 Myst4 54169 LIB 6527 0.17356428 0.192047589 0.15508097 -Myst4.6644 Myst4 54169 LIB 6644 2.400441106 2.029316862 2.771565351 -Nap1l1.2360 Nap1l1 53605 LIB 2360 0.319133892 0.437873007 0.200394778 -Nap1l1.2470 Nap1l1 53605 LIB 2470 2.672057204 0.893748358 4.45036605 -Nap1l1.3414 Nap1l1 53605 LIB 3414 0.391905722 0.627474398 0.156337047 -Nap1l1.3554 Nap1l1 53605 LIB 3554 0.112275278 0.113553114 0.110997442 -Nap1l2.819 Nap1l2 17954 LIB 819 2.125995207 0.800219962 3.451770452 -Nap1l2.1093 Nap1l2 17954 LIB 1093 0.088819529 0.018720495 0.158918562 -Nap1l2.1180 Nap1l2 17954 LIB 1180 6.48E-05 0.000129517 0 -Nap1l2.1695 Nap1l2 17954 LIB 1695 0.088807945 0.029942389 0.147673502 -Nap1l2.1750 Nap1l2 17954 LIB 1750 0.099698624 0.171510367 0.027886881 -Nap1l3.743 Nap1l3 54561 LIB 743 2.253593603 3.057823725 1.449363481 -Nap1l3.779 Nap1l3 54561 LIB 779 30.3934439 42.83344355 17.95344425 -Nap1l3.1969 Nap1l3 54561 LIB 1969 0.056225371 0.040622407 0.071828335 -Nap1l3.2063 Nap1l3 54561 LIB 2063 0.055599264 0.110335466 0.000863061 -Nap1l3.2498 Nap1l3 54561 LIB 2498 0.006560346 0.00966944 0.003451251 -Ncoa3.1032 Ncoa3 17979 LIB 1032 0.541947489 0.372010693 0.711884285 -Ncoa3.3669 Ncoa3 17979 LIB 3669 0.686557747 0.328572238 1.044543256 -Ncoa3.3815 Ncoa3 17979 LIB 3815 0.059493377 0 0.118986753 -Ncoa3.3885 Ncoa3 17979 LIB 3885 0.036495879 0.000121183 0.072870575 -Ncoa3.7494 Ncoa3 17979 LIB 7494 0.119249564 0.004346476 0.234152652 -Nr0b2.381 Nr0b2 23957 LIB 381 0.040594882 0.000521558 0.080668205 -Nr0b2.534 Nr0b2 23957 LIB 534 0.29750152 0.120015301 0.474987739 -Nr0b2.558 Nr0b2 23957 LIB 558 0.120666479 0.118932039 0.122400919 -Nr0b2.1023 Nr0b2 23957 LIB 1023 0.745556882 1.138253809 0.352859956 -Nr0b2.1068 Nr0b2 23957 LIB 1068 1.157353909 1.693199276 0.621508541 -Nsd1.2795 Nsd1 18193 LIB 2795 NA NA NA -Nsd1.5598 Nsd1 18193 LIB 5598 0.586999136 0.521905831 0.652092442 -Nsd1.5640 Nsd1 18193 LIB 5640 0.006176289 0.000922834 0.011429745 -Nsd1.11634 Nsd1 18193 LIB 11634 0.35901654 0.04608508 0.671947999 -Padi4.295 Padi4 18602 LIB 295 0.140719956 0.258960573 0.022479339 -Padi4.1042 Padi4 18602 LIB 1042 0.902821311 0.530879713 1.274762908 -Padi4.1058 Padi4 18602 LIB 1058 0.458948236 0.358981494 0.558914978 -Padi4.1914 Padi4 18602 LIB 1914 0.242089806 0.484052223 0.000127389 -Padi4.2336 Padi4 18602 LIB 2336 0.062117231 0.059119919 0.065114542 -Parp1.1124 Parp1 11545 LIB 1124 0.210888138 0.367549038 0.054227238 -Parp1.1623 Parp1 11545 LIB 1623 0.104470818 0.188126755 0.02081488 -Parp1.2887 Parp1 11545 LIB 2887 0.892550544 0.316455696 1.468645392 -Parp1.3789 Parp1 11545 LIB 3789 0.015223099 0.029524865 0.000921332 -Parp1.3790 Parp1 11545 LIB 3790 0.362609031 0.342329793 0.382888269 -Parp2.574 Parp2 11546 LIB 574 0.006105603 0.012211205 0 -Parp2.905 Parp2 11546 LIB 905 0.247891643 0.495783286 0 -Parp2.946 Parp2 11546 LIB 946 0.053243848 0.106487696 0 -Parp2.1006 Parp2 11546 LIB 1006 1.662743561 1.577856302 1.74763082 -Parp2.1429 Parp2 11546 LIB 1429 0.168234787 0.308182513 0.028287061 -Parp2.1677 Parp2 11546 LIB 1677 0.030777532 0.017032993 0.04452207 -Pax5.154 Pax5 18507 LIB 154 0.16139052 0.235338822 0.087442219 -Pax5.328 Pax5 18507 LIB 328 0.39397106 0.498357756 0.289584364 -Pax5.601 Pax5 18507 LIB 601 0.048479251 0.024589675 0.072368828 -Pax5.852 Pax5 18507 LIB 852 9.678858441 7.766500178 11.5912167 -Pax5.914 Pax5 18507 LIB 914 0.152719984 0.030076142 0.275363825 -Paxip1.3203 Paxip1 55982 LIB 3203 0.187420804 0.303786616 0.071054993 -Paxip1.3451 Paxip1 55982 LIB 3451 3.865093664 3.578045861 4.152141468 -Paxip1.3562 Paxip1 55982 LIB 3562 0.722329293 0.613098514 0.831560072 -Paxip1.3670 Paxip1 55982 LIB 3670 5.124811105 9.197264873 1.052357337 -Pcgf2.507 Pcgf2 22658 LIB 507 0.35115 0.32717803 0.375121969 -Pcgf2.690 Pcgf2 22658 LIB 690 0.084288102 0.160556564 0.00801964 -Pcgf2.801 Pcgf2 22658 LIB 801 0.09993849 0.068596738 0.131280242 -Pcgf2.982 Pcgf2 22658 LIB 982 0.444925531 0.384459989 0.505391072 -Pcgf2.1013 Pcgf2 22658 LIB 1013 0.090092787 5.67E-05 0.180128878 -Pcmt1.619 Pcmt1 18537 LIB 619 1.638746981 2.371052632 0.90644133 -Pcmt1.620 Pcmt1 18537 LIB 620 0.066119686 0.000258465 0.131980907 -Pcmt1.840 Pcmt1 18537 LIB 840 27.42358533 24.71543731 30.13173335 -Pcmt1.946 Pcmt1 18537 LIB 946 0.678912333 0.407078398 0.950746269 -Pcmt1.1259 Pcmt1 18537 LIB 1259 0.610136449 0.807828401 0.412444497 -Pcna.566 Pcna 18538 PC 566 0.013756331 0.021430795 0.006081866 -Pcna.1186 Pcna 18538 PC 1186 0 0 0 -Phf1.561 Phf1 21652 LIB 561 0.571926578 1.105404769 0.038448387 -Phf1.637 Phf1 21652 LIB 637 0.33142531 0.459700889 0.203149731 -Phf1.1098 Phf1 21652 LIB 1098 0.118527608 0.184246062 0.052809154 -Phf1.2400 Phf1 21652 LIB 2400 0.178047503 0.204710012 0.151384993 -Phf2.1851 Phf2 18676 LIB 1851 0.281793921 0.46524031 0.098347533 -Phf2.3668 Phf2 18676 LIB 3668 0.352946923 0.001776199 0.704117647 -Phf2.5132 Phf2 18676 LIB 5132 1.021354121 0.675807289 1.366900952 -Phf2.5166 Phf2 18676 LIB 5166 1.690348646 0.566009654 2.814687638 -Phf8.1420 Phf8 320595 LIB 1420 0.539886389 0.513086274 0.566686504 -Phf8.1984 Phf8 320595 LIB 1984 0.090594691 0.06110417 0.120085213 -Phf8.2131 Phf8 320595 LIB 2131 0.020983494 0.041486603 0.000480384 -Polr2b.489 Polr2b 231329 PC 489 0 0 0 -Polr2b.2176 Polr2b 231329 PC 2176 3.53E-05 7.06E-05 0 -Ppargc1a.669 Ppargc1a 19017 LIB 669 0.538610763 0.908737392 0.168484134 -Ppargc1a.831 Ppargc1a 19017 LIB 831 NA NA NA -Ppargc1a.1269 Ppargc1a 19017 LIB 1269 0.408904844 0.436043305 0.381766382 -Ppargc1a.1500 Ppargc1a 19017 LIB 1500 0.229797051 0.203566341 0.256027762 -Prdm1.711 Prdm1 12142 LIB 711 0.050370956 0.017908875 0.082833036 -Prdm1.862 Prdm1 12142 LIB 862 0.127106083 0.093023256 0.161188911 -Prdm1.919 Prdm1 12142 LIB 919 0.064288331 0.02643779 0.102138872 -Prdm1.2964 Prdm1 12142 LIB 2964 0.090658195 0.169964956 0.011351434 -Prdm1.3709 Prdm1 12142 LIB 3709 0.964704579 0.430668605 1.498740554 -Prdm10.318 Prdm10 382066 LIB 318 0.06919639 0.042373324 0.096019455 -Prdm10.1130 Prdm10 382066 LIB 1130 0.161461455 0.167124645 0.155798265 -Prdm10.1348 Prdm10 382066 LIB 1348 0.121409823 0.178588808 0.064230838 -Prdm10.2613 Prdm10 382066 LIB 2613 0.275005354 0.550010709 0 -Prdm11.1844 Prdm11 100042784 LIB 1844 0.049836641 0.003384095 0.096289187 -Prdm11.2306 Prdm11 100042784 LIB 2306 0.106674086 0.187523208 0.025824964 -Prdm11.3215 Prdm11 100042784 LIB 3215 0.248260853 0.357676324 0.138845382 -Prdm11.3216 Prdm11 100042784 LIB 3216 0.162689304 0.102281495 0.223097113 -Prdm12.481 Prdm12 381359 LIB 481 0.121026312 9.03E-05 0.241962372 -Prdm12.603 Prdm12 381359 LIB 603 0.11654652 0.146549398 0.086543642 -Prdm12.1421 Prdm12 381359 LIB 1421 0.036882594 0.001164353 0.072600834 -Prdm12.2351 Prdm12 381359 LIB 2351 0.862186131 0.987938749 0.736433513 -Prdm13.554 Prdm13 230025 LIB 554 0.060698903 0.02212727 0.099270536 -Prdm13.2613 Prdm13 230025 LIB 2613 5.270386453 3.099350703 7.441422202 -Prdm13.2702 Prdm13 230025 LIB 2702 0.521784232 0 1.043568465 -Prdm13.2828 Prdm13 230025 LIB 2828 0.075151234 0.112102387 0.038200081 -Prdm13.2936 Prdm13 230025 LIB 2936 0.269317079 0.20276676 0.335867398 -Prdm14.530 Prdm14 383491 LIB 530 0.405412499 0.39411959 0.416705408 -Prdm14.1756 Prdm14 383491 LIB 1756 0.005945122 0 0.011890244 -Prdm14.1934 Prdm14 383491 LIB 1934 0.293485392 0.527073733 0.059897052 -Prdm14.2271 Prdm14 383491 LIB 2271 0.111037316 0.097569355 0.124505277 -Prdm14.2348 Prdm14 383491 LIB 2348 0.492448295 0.042176871 0.94271972 -Prdm15.958 Prdm15 114604 LIB 958 0.98252896 1.932489451 0.032568468 -Prdm15.1034 Prdm15 114604 LIB 1034 0.004062756 0.003733333 0.004392179 -Prdm15.1690 Prdm15 114604 LIB 1690 0.524906994 0.429446747 0.620367241 -Prdm15.1796 Prdm15 114604 LIB 1796 0.174355348 0.183572542 0.165138154 -Prdm15.2734 Prdm15 114604 LIB 2734 0.038957255 0.003943577 0.073970934 -Prdm16.680 Prdm16 70673 LIB 680 0.533914395 0.660762545 0.407066246 -Prdm16.5683 Prdm16 70673 LIB 5683 0.096716361 0.180946552 0.01248617 -Prdm16.8212 Prdm16 70673 LIB 8212 NA NA NA -Prdm16.8363 Prdm16 70673 LIB 8363 0.430720448 0.248793956 0.61264694 -Prdm16.8571 Prdm16 70673 LIB 8571 2.329170058 2.550566982 2.107773134 -Prdm2.1020 Prdm2 110593 LIB 1020 0.153596644 0.259297344 0.047895945 -Prdm2.4191 Prdm2 110593 LIB 4191 0.559676498 0.502441293 0.616911704 -Prdm2.4655 Prdm2 110593 LIB 4655 NA NA NA -Prdm2.4956 Prdm2 110593 LIB 4956 0.090352843 0.160106435 0.020599251 -Prdm2.5781 Prdm2 110593 LIB 5781 0.2845147 0.353298153 0.215731247 -Prdm4.1943 Prdm4 72843 LIB 1943 0.115287664 0.047414054 0.183161274 -Prdm4.2535 Prdm4 72843 LIB 2535 0.085408022 0.000193199 0.170622844 -Prdm4.3139 Prdm4 72843 LIB 3139 0.001128668 0 0.002257336 -Prdm4.3391 Prdm4 72843 LIB 3391 0.069371374 0.05967095 0.079071797 -Prdm4.3667 Prdm4 72843 LIB 3667 NA NA NA -Prdm5.908 Prdm5 70779 LIB 908 0.149313429 0.128342246 0.170284612 -Prdm5.984 Prdm5 70779 LIB 984 0.413409055 0.622305737 0.204512373 -Prdm5.1353 Prdm5 70779 LIB 1353 1.643969827 2.094062103 1.193877551 -Prdm5.2148 Prdm5 70779 LIB 2148 0.648213784 0.715798492 0.580629076 -Prdm6.1018 Prdm6 225518 LIB 1018 0.009633756 0.011159403 0.008108108 -Prdm6.1790 Prdm6 225518 LIB 1790 0.123211194 0.098809823 0.147612565 -Prdm6.1823 Prdm6 225518 LIB 1823 0.328175562 0.377128018 0.279223106 -Prdm6.1839 Prdm6 225518 LIB 1839 0.201249487 0.337440758 0.065058216 -Prdm8.2290 Prdm8 77630 LIB 2290 0.000542104 0.00048216 0.000602047 -Prdm8.3042 Prdm8 77630 LIB 3042 3.233747051 5.976620158 0.490873944 -Prdm8.3048 Prdm8 77630 LIB 3048 0.640755782 1.166720727 0.114790837 -Prdm8.3062 Prdm8 77630 LIB 3062 0.361793005 0.256726293 0.466859717 -Prdm9.77 Prdm9 213389 LIB 77 0.401141561 0.283516221 0.518766901 -Prdm9.496 Prdm9 213389 LIB 496 0.222497616 0.078468537 0.366526695 -Prdm9.1838 Prdm9 213389 LIB 1838 0.302877526 0.400302009 0.205453043 -Prkaa1.145 Prkaa1 105787 LIB 145 0.14165733 0.1690104 0.114304261 -Prkaa1.1981 Prkaa1 105787 LIB 1981 0.019533353 0.019407151 0.019659554 -Prkaa1.3080 Prkaa1 105787 LIB 3080 NA NA NA -Prkaa1.3635 Prkaa1 105787 LIB 3635 3.189719542 4.278249106 2.101189977 -Prkaa1.3954 Prkaa1 105787 LIB 3954 0.013169577 0 0.026339154 -Prkaa1.4596 Prkaa1 105787 LIB 4596 0.034088344 0.058964593 0.009212095 -Prkaa2.2299 Prkaa2 108079 LIB 2299 0.004331754 0.000484027 0.008179481 -Prkaa2.2748 Prkaa2 108079 LIB 2748 0.340786503 0.362280234 0.319292772 -Prkaa2.4825 Prkaa2 108079 LIB 4825 NA NA NA -Prkaa2.6172 Prkaa2 108079 LIB 6172 0.020265668 0 0.040531335 -Prkaa2.6849 Prkaa2 108079 LIB 6849 0.135065674 0.072316173 0.197815176 -Prkcd.161 Prkcd 18753 LIB 161 0.179448269 0.099882029 0.259014509 -Prkcd.441 Prkcd 18753 LIB 441 0.327507015 0.001459854 0.653554175 -Prkcd.707 Prkcd 18753 LIB 707 0.664294206 1.071999112 0.2565893 -Prkcd.1389 Prkcd 18753 LIB 1389 1.255652224 0.641311475 1.869992973 -Prmt1.243 Prmt1 15469 LIB 243 0.110664823 0.120254845 0.101074802 -Prmt1.264 Prmt1 15469 LIB 264 0.272777523 0.382384883 0.163170163 -Prmt1.630 Prmt1 15469 LIB 630 1.328852347 1.764027294 0.8936774 -Prmt1.1014 Prmt1 15469 LIB 1014 0.484140888 0.638219895 0.330061882 -Prmt2.151 Prmt2 15468 LIB 151 0.031631618 0.037750897 0.025512338 -Prmt2.154 Prmt2 15468 LIB 154 0.973162231 1.211030345 0.735294118 -Prmt2.1066 Prmt2 15468 LIB 1066 9.18E-05 0.000183688 0 -Prmt2.1067 Prmt2 15468 LIB 1067 0.815640774 0.654386731 0.976894818 -Prmt3.502 Prmt3 71974 LIB 502 0.157500935 0.315001871 0 -Prmt3.814 Prmt3 71974 LIB 814 4.89E-05 0 9.79E-05 -Prmt3.838 Prmt3 71974 LIB 838 3.559311442 4.211350585 2.907272299 -Prmt3.985 Prmt3 71974 LIB 985 0.274535697 0.423260006 0.125811388 -Prmt3.1839 Prmt3 71974 LIB 1839 0.113816928 0.148898678 0.078735178 -Prmt5.56 Prmt5 27374 LIB 56 0.778904793 0.453405018 1.104404568 -Prmt5.266 Prmt5 27374 LIB 266 0.201764199 0.173979378 0.22954902 -Prmt5.2152 Prmt5 27374 LIB 2152 0.126875652 0.076575692 0.177175612 -Prmt5.2293 Prmt5 27374 LIB 2293 2.188455879 0.469499821 3.907411937 -Prmt6.247 Prmt6 99890 LIB 247 0.033732942 0.000853242 0.066612642 -Prmt6.1493 Prmt6 99890 LIB 1493 0.134310673 0.232186732 0.036434613 -Prmt6.1983 Prmt6 99890 LIB 1983 0.154846836 0.167501928 0.142191745 -Prmt6.2355 Prmt6 99890 LIB 2355 0.50072786 0.541981695 0.459474025 -Prmt7.23 Prmt7 214572 LIB 23 0.009433344 0.004819277 0.01404741 -Prmt7.45 Prmt7 214572 LIB 45 0.543933929 0.518786922 0.569080936 -Prmt7.88 Prmt7 214572 LIB 88 0.080612502 0.04869904 0.112525964 -Prmt7.1284 Prmt7 214572 LIB 1284 0.06501016 0.126209284 0.003811036 -Prmt7.2135 Prmt7 214572 LIB 2135 0.23497578 0.386599091 0.083352468 -Prmt8.302 Prmt8 381813 LIB 302 0.244600451 0.198269736 0.290931167 -Prmt8.455 Prmt8 381813 LIB 455 0.59669119 0.802821189 0.390561191 -Prmt8.667 Prmt8 381813 LIB 667 0.045662786 0.087305569 0.004020002 -Prmt8.1854 Prmt8 381813 LIB 1854 0.108178455 0.06973876 0.146618151 -Psip1.763 Psip1 101739 LIB 763 0.008304892 0 0.016609784 -Psip1.1311 Psip1 101739 LIB 1311 0 0 0 -Psip1.1596 Psip1 101739 LIB 1596 0.059717843 0.087169563 0.032266123 -Psip1.2474 Psip1 101739 LIB 2474 0.006237689 0.012475378 0 -Psip1.2652 Psip1 101739 LIB 2652 0.06194056 0.10699453 0.016886591 -Rbbp4.2088 Rbbp4 19646 LIB 2088 0.193789327 0.126048165 0.261530489 -Rbbp4.2174 Rbbp4 19646 LIB 2174 0.005813953 0 0.011627907 -Rbbp4.2511 Rbbp4 19646 LIB 2511 0.928220759 1.004589667 0.851851852 -Rbbp4.3753 Rbbp4 19646 LIB 3753 0.073360623 0.135745027 0.010976218 -Rbbp5.1634 Rbbp5 213464 LIB 1634 1.015990856 1.156510409 0.875471303 -Rbbp5.2248 Rbbp5 213464 LIB 2248 0.000789875 0.00145743 0.00012232 -Rbbp5.2655 Rbbp5 213464 LIB 2655 0.121958567 0.170557717 0.073359417 -Rbbp5.2974 Rbbp5 213464 LIB 2974 1.399302063 1.445902998 1.352701127 -Renilla.713 Renilla Luciferase NC 713 1.666788004 1.533762916 1.799813091 -Ring1.260 Ring1 19763 LIB 260 0.286061741 0.026611473 0.54551201 -Ring1.669 Ring1 19763 LIB 669 0.165118469 0.170742026 0.159494912 -Ring1.1034 Ring1 19763 LIB 1034 0.180669238 0.016304348 0.345034127 -Rnf2.1856 Rnf2 19821 LIB 1856 0.673388184 0.833867094 0.512909274 -Rnf2.2203 Rnf2 19821 LIB 2203 0.954595303 0.850564925 1.05862568 -Rnf2.2538 Rnf2 19821 LIB 2538 0.837959761 0.541602515 1.134317006 -Rnf2.2809 Rnf2 19821 LIB 2809 0.187347204 0.081992104 0.292702304 -Rnf2.2875 Rnf2 19821 LIB 2875 0.546987675 0.692397599 0.401577752 -Rnf20.420 Rnf20 109331 LIB 420 0.063920224 0.054351697 0.073488751 -Rnf20.948 Rnf20 109331 LIB 948 0.278768206 0.423430663 0.134105749 -Rnf20.1295 Rnf20 109331 LIB 1295 0.000109004 0 0.000218007 -Rnf20.3244 Rnf20 109331 LIB 3244 NA NA NA -Rnf20.3277 Rnf20 109331 LIB 3277 0.459938908 0.803347787 0.11653003 -Rnf20.3718 Rnf20 109331 LIB 3718 1.136821022 1.414336918 0.859305126 -Rpa1.1620 Rpa1 68275 PC 1620 0.007210873 0.000351973 0.014069774 -Rpa3.276 Rpa3 68240 PC 278 7.32E-05 0.000111564 3.48E-05 -Rpa3.455 Rpa3 68240 PC 457 0.018174308 0.02069689 0.015651726 -Rpa3.561 Rpa3 68240 PC 561 0.00476048 0.002574918 0.006946042 -Satb1.710 Satb1 20230 LIB 710 0.161960667 0.323389702 0.000531632 -Satb1.1401 Satb1 20230 LIB 1401 0.392569667 0.3563288 0.428810533 -Satb1.1478 Satb1 20230 LIB 1478 0.24003152 0.473695747 0.006367292 -Satb1.1709 Satb1 20230 LIB 1709 0.193635318 0.075057818 0.312212817 -Satb1.2566 Satb1 20230 LIB 2566 0.193845463 0.035309973 0.352380952 -Setd1a.119 Setd1a 233904 LIB 119 0.107452217 0.170620438 0.044283995 -Setd1a.388 Setd1a 233904 LIB 388 0.608381477 0.653331355 0.5634316 -Setd1a.643 Setd1a 233904 LIB 643 1.521441453 1.691804708 1.351078197 -Setd1a.5859 Setd1a 233904 LIB 5859 0.797831182 0.900645478 0.695016886 -Setd1b.3553 Setd1b 208043 LIB 3553 8.23E-05 0 0.0001646 -Setd1b.3557 Setd1b 208043 LIB 3557 0.18069148 0.180119102 0.181263858 -Setd1b.4520 Setd1b 208043 LIB 4520 0.199934074 0.05129672 0.348571429 -Setd1b.4522 Setd1b 208043 LIB 4522 0.003342509 0 0.006685018 -Setd1b.4699 Setd1b 208043 LIB 4699 0.137405083 0.097939189 0.176870978 -Setd2.182 Setd2 235626 LIB 182 0.040179039 0.047492416 0.032865662 -Setd2.1467 Setd2 235626 LIB 1467 0.00017313 0 0.00034626 -Setd2.1785 Setd2 235626 LIB 1785 0.038294803 0.027488932 0.049100673 -Setd2.3632 Setd2 235626 LIB 3632 0.377349359 0.44562685 0.309071868 -Setd2.4051 Setd2 235626 LIB 4051 0 0 0 -Setd3.795 Setd3 52690 LIB 795 0.126767545 0.027322404 0.226212687 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Setdb1 84505 LIB 3684 0.010401671 8.66E-05 0.02071677 -Setdb2.809 Setdb2 239122 LIB 809 1.391206827 2.779885057 0.002528597 -Setdb2.810 Setdb2 239122 LIB 810 1.190095337 0.963319847 1.416870827 -Setdb2.990 Setdb2 239122 LIB 990 0.079364105 0.021533706 0.137194504 -Setdb2.1417 Setdb2 239122 LIB 1417 0.34737866 0.393661661 0.30109566 -Setmar.1193 Setmar 74729 LIB 1193 0.292843192 0.358163209 0.227523174 -Setmar.1195 Setmar 74729 LIB 1195 0.162091025 0.135760257 0.188421792 -Setmar.1589 Setmar 74729 LIB 1589 64.11298219 52.14726514 76.07869924 -Sfmbt1.868 Sfmbt1 54650 LIB 868 1.013294698 1.206846418 0.819742977 -Sfmbt1.1345 Sfmbt1 54650 LIB 1345 0.008587566 0.010476801 0.006698332 -Sfmbt1.1802 Sfmbt1 54650 LIB 1802 1.004772904 0.72139738 1.288148429 -Sfmbt1.2018 Sfmbt1 54650 LIB 2018 0.26726547 0.475359343 0.059171598 -Sfmbt1.2421 Sfmbt1 54650 LIB 2421 0.075539295 0.001624805 0.149453785 -Sfmbt2.602 Sfmbt2 353282 LIB 602 0.281181984 0.520202721 0.042161246 -Sfmbt2.3592 Sfmbt2 353282 LIB 3592 0.082878502 0.005644644 0.16011236 -Sfmbt2.5673 Sfmbt2 353282 LIB 5673 0.134401376 0.019676674 0.249126078 -Sin3a.531 Sin3a 20466 LIB 531 0 0 0 -Sin3a.3537 Sin3a 20466 LIB 3537 0.024340683 0 0.048681366 -Sin3a.3559 Sin3a 20466 LIB 3559 1.728939777 2.831898734 0.62598082 -Sin3a.4729 Sin3a 20466 LIB 4729 0 0 0 -Sin3b.188 Sin3b 20467 LIB 188 0.042293799 0.084587598 0 -Sin3b.326 Sin3b 20467 LIB 326 1.438726271 2.275190706 0.602261836 -Sin3b.338 Sin3b 20467 LIB 338 0.105590062 0 0.211180124 -Sin3b.381 Sin3b 20467 LIB 381 0.134926536 0.248162305 0.021690768 -Sin3b.475 Sin3b 20467 LIB 475 0.639579924 1.118636662 0.160523187 -Sirt1.688 Sirt1 93759 LIB 688 1.451209242 1.979805805 0.922612678 -Sirt1.1708 Sirt1 93759 LIB 1708 0.631165203 0.733237638 0.529092768 -Sirt1.1779 Sirt1 93759 LIB 1779 0.436869096 0.336818563 0.536919629 -Sirt1.2191 Sirt1 93759 LIB 2191 1.729713563 2.528467711 0.930959415 -Sirt2.735 Sirt2 64383 LIB 735 0.147707432 0.003062938 0.292351926 -Sirt2.1418 Sirt2 64383 LIB 1418 0.131476192 0.093366665 0.169585719 -Sirt2.1460 Sirt2 64383 LIB 1460 0.276894538 0.290329505 0.26345957 -Sirt2.1600 Sirt2 64383 LIB 1600 0.023729675 0.026015228 0.021444122 -Sirt3.462 Sirt3 64384 LIB 462 0.43015768 0.70883566 0.1514797 -Sirt3.869 Sirt3 64384 LIB 869 0.087373128 0.032567568 0.142178688 -Sirt3.993 Sirt3 64384 LIB 993 1.118453529 1.035942224 1.200964834 -Sirt3.1002 Sirt3 64384 LIB 1002 0.316055067 0.208823529 0.423286604 -Sirt3.1236 Sirt3 64384 LIB 1236 0.23257166 0.248811512 0.216331808 -Sirt4.105 Sirt4 75387 LIB 105 0.787448713 0.84617509 0.728722336 -Sirt4.633 Sirt4 75387 LIB 633 0.413766331 0.018150999 0.809381663 -Sirt4.1490 Sirt4 75387 LIB 1490 0.271724181 0.467032967 0.076415394 -Sirt4.1806 Sirt4 75387 LIB 1806 0.211146978 0.364117918 0.058176038 -Sirt5.586 Sirt5 68346 LIB 586 0.04315097 0.061098763 0.025203178 -Sirt5.1032 Sirt5 68346 LIB 1032 NA NA NA -Sirt5.1219 Sirt5 68346 LIB 1219 1.159282043 1.459821841 0.858742245 -Sirt5.1290 Sirt5 68346 LIB 1290 0.148949431 0.165555092 0.132343769 -Sirt6.83 Sirt6 50721 LIB 83 0.036022476 0.05303979 0.019005162 -Sirt6.421 Sirt6 50721 LIB 421 0.000122991 0 0.000245982 -Sirt6.937 Sirt6 50721 LIB 937 0.232027633 0.160600291 0.303454974 -Sirt6.1609 Sirt6 50721 LIB 1609 0.364602844 0.086260111 0.642945578 -Sirt7.841 Sirt7 209011 LIB 841 0 0 0 -Sirt7.844 Sirt7 209011 LIB 844 0.221531023 0.111507818 0.331554227 -Sirt7.1238 Sirt7 209011 LIB 1238 0.21552915 0.207286174 0.223772125 -Sirt7.1604 Sirt7 209011 LIB 1604 0.118405846 0.003893381 0.232918312 -Sirt7.1677 Sirt7 209011 LIB 1677 0.451595828 0.535251456 0.367940199 -Smarca1.1401 Smarca1 93761 LIB 1401 1.153548695 1.688711584 0.618385807 -Smarca1.1430 Smarca1 93761 LIB 1430 0.46036335 0.786028584 0.134698116 -Smarca1.1613 Smarca1 93761 LIB 1613 0.11066776 0.061904944 0.159430577 -Smarca1.1893 Smarca1 93761 LIB 1893 0.213806299 0.218937644 0.208674954 -Smarca1.3418 Smarca1 93761 LIB 3418 0.607874304 1.091527057 0.124221551 -Smarca2.263 Smarca2 67155 LIB 263 0.172543567 0.178539893 0.166547241 -Smarca2.274 Smarca2 67155 LIB 274 0 0 0 -Smarca2.712 Smarca2 67155 LIB 712 0.035563959 0.003878282 0.067249636 -Smarca2.1061 Smarca2 67155 LIB 1061 0.08050899 0.120002107 0.041015873 -Smarca4.3232 Smarca4 20586 LIB 3232 0 0 0 -Smarca4.3364 Smarca4 20586 LIB 3364 0.185891845 0 0.371783689 -Smarca4.3633 Smarca4 20586 LIB 3633 0.101871507 0.169502565 0.03424045 -Smarca4.4935 Smarca4 20586 LIB 4935 0.464028994 0.638482699 0.28957529 -Smarca4.5466 Smarca4 20586 LIB 5466 0 0 0 -Smarca5.1139 Smarca5 93762 LIB 1139 39.02044459 29.48150462 48.55938456 -Smarca5.1264 Smarca5 93762 LIB 1264 0.051361802 0.102723605 0 -Smarca5.3886 Smarca5 93762 LIB 3886 2.889445252 4.275900073 1.502990431 -Smarca5.4421 Smarca5 93762 LIB 4421 0.027038126 0.047147846 0.006928406 -Smarca5.4522 Smarca5 93762 LIB 4522 1.659875833 1.301821998 2.017929668 -Smarcc2.1398 Smarcc2 68094 LIB 1398 5.667513887 8.025575273 3.309452502 -Smarcc2.1941 Smarcc2 68094 LIB 1941 0.671956498 0.125396825 1.21851617 -Smarcc2.2235 Smarcc2 68094 LIB 2235 0.277627685 0.414749573 0.140505797 -Smarcc2.2541 Smarcc2 68094 LIB 2541 0.369172133 0.397641112 0.340703153 -Smarcd1.690 Smarcd1 83797 LIB 690 0.029841397 0.009797964 0.049884831 -Smarcd1.986 Smarcd1 83797 LIB 986 0.145361327 0.246381645 0.044341009 -Smarcd1.1738 Smarcd1 83797 LIB 1738 0.763237236 1.299479167 0.226995305 -Smarcd1.1858 Smarcd1 83797 LIB 1858 0.19664493 0.30078986 0.0925 -Smarcd3.518 Smarcd3 66993 LIB 518 0.109320414 0.188431483 0.030209345 -Smarcd3.847 Smarcd3 66993 LIB 847 0.27744907 0.176790744 0.378107396 -Smarcd3.1323 Smarcd3 66993 LIB 1323 0.345474467 0.457416001 0.233532934 -Smarcd3.1591 Smarcd3 66993 LIB 1591 0.117582645 0.231035335 0.004129956 -Smarcd3.1708 Smarcd3 66993 LIB 1708 0 0 0 -Smarce1.2096 Smarce1 57376 LIB 2096 0.225624714 0.208014266 0.243235162 -Smarce1.2121 Smarce1 57376 LIB 2121 5.976009675 3.943683037 8.008336314 -Smarce1.2154 Smarce1 57376 LIB 2154 0.166161562 0.03823709 0.294086035 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0.124362265 0.177337952 0.071386579 -Smyd4.3333 Smyd4 319822 LIB 3333 0.281233349 0.168597717 0.393868982 -Smyd4.3414 Smyd4 319822 LIB 3414 0.036082039 0.064381611 0.007782466 -Smyd4.3439 Smyd4 319822 LIB 3439 0.102705754 0.118006231 0.087405278 -Smyd5.1548 Smyd5 232187 LIB 1548 0.555290132 1.105784101 0.004796163 -Smyd5.1643 Smyd5 232187 LIB 1643 0.201223576 0.237695287 0.164751865 -Smyd5.2044 Smyd5 232187 LIB 2044 0.100536441 0 0.201072882 -Smyd5.2048 Smyd5 232187 LIB 2048 4.496682919 5.749585661 3.243780178 -Srcap.2697 Srcap 100043597 LIB 2697 0.349388033 0 0.698776065 -Srcap.3130 Srcap 100043597 LIB 3130 0.212521996 0.244648899 0.180395093 -Srcap.5342 Srcap 100043597 LIB 5342 0.052050563 0.074190594 0.029910532 -Srcap.7360 Srcap 100043597 LIB 7360 0.000185048 0.000370096 0 -Srcap.11381 Srcap 100043597 LIB 11381 0.306910194 0.366298636 0.247521752 -Ssrp1.306 Ssrp1 20833 LIB 306 0.130932283 0 0.261864566 -Ssrp1.577 Ssrp1 20833 LIB 577 0 0 0 -Ssrp1.897 Ssrp1 20833 LIB 897 0 0 0 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