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ggCDPbamv1.R
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# CDP PLOT Version 1
# AUTHOR: AMIR MANZOUR
ggCDPbamv1 <- function(## INPUTS
minTPM = 5,
maxTPM = Inf,
minintron = 5,
minexon = 5,
minExtensionRatio = 0.1,
absminTPM = 1,
absminintron = 1,
absminexon = 1,
absminExtensionRatio = 0.05,
minTxSize = 500,
minIntronSize = 200,
minExonSize = 500,
Extension = 1000,
overlapcoef=0.95,
RNAseqLengthNormalize=TRUE,
PARCLIPLengthNormalize = TRUE,
readlength=50,
minoverlapOnIntrons=25,
minoverlapOnExons=25,
gtfpath = NULL,
myWTpaths = NULL,
myTreatmentpaths = NULL,
myPARCLIPpath = NULL,
returnAll = FALSE,
MasterTableOriginal = NULL,
MasterTable = NULL,
ispairedendreadtext = "single-read",
ispairedendread=FALSE,
Only24chromosomes=TRUE,
ReverseBamFileStrand=TRUE,
FilterPseudogenes=TRUE,
FilterAntisense=TRUE,
TargetTolerance=50,
ignoreParclipStrand = FALSE,
#====CDF parameters
includeBin0 = TRUE,
plotByColumn="log2fC",
binColumn="PARCLIPgene",
histBreaks=1000,
seehistogram=FALSE,
binNames=c("bin0","bin1","bin2","bin3","bin4"),
exprNormalization = TRUE,
## GGPLOT PARAMETERS
fontFamily = "Helvetica",
legendTitle = c("Bin","genes","median","pval"),
legendTextSize = 5,
legendPosition = c(1.5,0.5),
limitsX = c(-2.5,2.5),
pointSize = 1,
lineSize = 0.2,
panelBorderSize = 0.5,
legendSpacing = 0.5,
xlab = "Log2 Fold Change [Treatment/WT]",
ylab = "Cumulative Distribution",
axisTitleSize = 8,
axisTextSize = 8,
ggTitleSize = 5,
AnalysisName = NULL
){
## //LIBRARIES
## ............
suppressWarnings(suppressMessages(library(data.table)))
suppressWarnings(suppressMessages(library(plyr)))
suppressWarnings(suppressMessages(library(dplyr)))
suppressWarnings(suppressMessages(library(reshape2)))
suppressWarnings(suppressMessages(library(GenomicFeatures)))
suppressWarnings(suppressMessages(library(GenomicRanges)))
suppressWarnings(suppressMessages(library(GenomeInfoDb)))
suppressWarnings(suppressMessages(library(Rsamtools)))
suppressWarnings(suppressMessages(library(GenomicAlignments)))
suppressWarnings(suppressMessages(library(ggplot2)))
suppressWarnings(suppressMessages(library(gplots)))
suppressWarnings(suppressMessages(library(RColorBrewer)))
suppressWarnings(suppressMessages(library(extrafont)))
suppressWarnings(suppressMessages(library(grid)))
suppressWarnings(suppressMessages(library(gridExtra)))
suppressWarnings(suppressMessages(library(reporttools)))
suppressWarnings(suppressMessages(library(rtracklayer)))
# suppressWarnings(suppressMessages(library(MVN)))
suppressWarnings(suppressMessages(library(ggrepel)))
suppressWarnings(suppressMessages(library(plyr)))
suppressWarnings(suppressMessages(library(dplyr)))
suppressWarnings(suppressMessages(library(ggpubr)))
suppressWarnings(suppressMessages(library(plotly)))
# suppressWarnings(suppressMessages(library(idr)))
# suppressWarnings(suppressMessages(library(htmlwidgets)))
# suppressWarnings(suppressMessages(library(ggfortify)))
# suppressWarnings(suppressMessages(library(mclust)))
# suppressWarnings(suppressMessages(library(DESeq2)))
# Make Master Table
if(is.null(MasterTable) == TRUE) {
# make sure necessary files are in input
if(is.null(myPARCLIPpath) == TRUE){stop("You forgot to include the PAR-CLIP XL bam file(s).")}
if(is.null(myWTpaths) == TRUE){stop("You forgot to include WT RNA-seq bam files.")}
if(is.null(myTreatmentpaths) == TRUE){stop("You forgot to include Treatment RNA-seq bam file(s).")}
if(is.null(gtfpath) == TRUE){stop("You forgot to include the gtf file.")}
message("constructing gene annotations...")
# Reading GTF file
gtftable <- rtracklayer::import(gtfpath)
gtf=as.data.frame(gtftable)
setDT(gtf)
if ("gene_type" %in% colnames(gtf) & dim(gtf[type == "gene",c("gene_id","gene_name")])[1] > 0) {
gene_names_types <- gtf[type == "gene",c("gene_id","gene_name","gene_type")]
} else {
gene_names_types <- gtf[type == "start_codon",c("gene_id","gene_name")]
gene_names_types[["gene_type"]] <- gene_names_types[["gene_name"]]
}
setDT(gene_names_types)
txdb <- GenomicFeatures::makeTxDbFromGFF(file = gtfpath, format = "gtf", organism = "Homo sapiens")
# PREPARE GENE COORDINATES
genes_GRangelist <- GenomicFeatures::genes(txdb)
if (Only24chromosomes){
chromosomecount=24
} else {
chromosomecount=length(GenomeInfoDb::seqlevels(genes_GRangelist))
}
genes_GRangelist <- genes_GRangelist[GenomicRanges::seqnames(genes_GRangelist) %in% GenomeInfoDb::seqlevels(genes_GRangelist)[1:chromosomecount], ]
transcriptInfo <- transcriptLengths(txdb = txdb, with.cds_len = TRUE, with.utr5_len = TRUE, with.utr3_len = TRUE)
transcriptInfo <- as.data.frame(transcriptInfo)
setDT(transcriptInfo)
geneID <- transcriptInfo[, .SD[which.max(tx_len)], by = gene_id]
geneID <- as.data.frame(geneID)
setDT(geneID)
geneInfo <-base::merge(geneID,gene_names_types, by = "gene_id", all.x = TRUE)
geneInfo <-geneInfo[,c("gene_id","tx_len","gene_name","gene_type"),with=FALSE]
m <- match(mcols(genes_GRangelist)$gene_id, geneInfo$gene_id)
mcols(genes_GRangelist) <- cbind(mcols(genes_GRangelist), geneInfo[m, -1L, drop=FALSE])
# INTRON COORDINATES
myintrons <- GenomicFeatures::intronsByTranscript(txdb, use.names=TRUE)
# constrain introns on gene coordinates:
myintrons_unlist <- unlist(myintrons)
mygeneoverlaps <- findOverlaps(myintrons_unlist, genes_GRangelist)
myintrons_unlist_ingenes <- myintrons_unlist[queryHits(mygeneoverlaps)]
mcols(myintrons_unlist_ingenes)$gene_id <- genes_GRangelist[subjectHits(mygeneoverlaps)]$gene_id
myintrons_unlist_ingenes_reduced <- reduce(myintrons_unlist_ingenes, drop.empty.ranges=TRUE,with.revmap=TRUE)
myrevmap1 <- mcols(myintrons_unlist_ingenes_reduced)$revmap
myrevmap1gene_id <- relist(mcols(myintrons_unlist_ingenes)[unlist(myrevmap1), ], myrevmap1)
mcols(myintrons_unlist_ingenes_reduced)$gene_id <- unlist(lapply(myrevmap1gene_id, function(x) x[1]))
# exclude exons
exonsdub <- GenomicFeatures::exons(txdb, use.names=TRUE)
exons_reduced <-reduce(exonsdub)
myintrons_unlist_ingenes_reduced_diff <- setdiff(myintrons_unlist_ingenes_reduced, exons_reduced,ignore.strand=F)
myintrons_unlist_ingenes_reduced_exoncleaned <- myintrons_unlist_ingenes_reduced[subjectHits(findOverlaps(myintrons_unlist_ingenes_reduced_diff, myintrons_unlist_ingenes_reduced))]
myintrons_unlist_ingenes_reduced_exoncleaned_reduced <- reduce(myintrons_unlist_ingenes_reduced_exoncleaned, drop.empty.ranges=TRUE,with.revmap=TRUE)
myrevmap2 <- mcols(myintrons_unlist_ingenes_reduced_exoncleaned_reduced)$revmap
myrevmap2gene_id <- relist(mcols(myintrons_unlist_ingenes_reduced_exoncleaned)[unlist(myrevmap2), "gene_id"], myrevmap2)
mcols(myintrons_unlist_ingenes_reduced_exoncleaned_reduced)$gene_id <- unlist(lapply(myrevmap2gene_id, function(x) x[1]))
intronsfinalall <- myintrons_unlist_ingenes_reduced_exoncleaned_reduced
#CDS coordinates
cds <- GenomicFeatures::cdsBy(txdb, by="gene", use.names=FALSE)
cds_unlist <- unlist(cds, use.names=TRUE)
mcols(cds_unlist)$gene_id <- names(cds_unlist)
#Exon coordinates
exonsdub_unlist <- exonsdub
mygeneoverlapsexon <- findOverlaps(exonsdub_unlist, genes_GRangelist)
exonsdub_unlist_ingenes <- exonsdub_unlist[queryHits(mygeneoverlapsexon)]
mcols(exonsdub_unlist_ingenes)$gene_id <- genes_GRangelist[subjectHits(mygeneoverlapsexon)]$gene_id
exonsdub_unlist_ingenes_reduced <- reduce(exonsdub_unlist_ingenes, drop.empty.ranges=TRUE,with.revmap=TRUE)
myrevmap1ex <- mcols(exonsdub_unlist_ingenes_reduced)$revmap
myrevmap1exgene_id <- relist(mcols(exonsdub_unlist_ingenes)[unlist(myrevmap1ex), "gene_id"], myrevmap1ex)
mcols(exonsdub_unlist_ingenes_reduced)$gene_id <- unlist(lapply(myrevmap1exgene_id, function(x) x[1]))
exonsall <- exonsdub_unlist_ingenes_reduced
#genes_GRangelist <- genes_GRangelist[GenomicRanges::seqnames(genes_GRangelist) %in% GenomeInfoDb::seqlevels(genes_GRangelist)[1:chromosomecount], ]
# 3UTR extension
fragment = readlength
utr3_by_gene_flankraw1 <- flank(genes_GRangelist, width=fragment, start=FALSE, both=FALSE, use.names=TRUE, ignore.strand=FALSE)
utr3_by_gene_flankraw <- flank(utr3_by_gene_flankraw1, width=Extension, start=FALSE, both=FALSE, use.names=TRUE, ignore.strand=FALSE)
utr3_by_gene_flank <- utr3_by_gene_flankraw[-queryHits(GenomicRanges::findOverlaps(utr3_by_gene_flankraw, genes_GRangelist, type="any")),]
utr3_by_gene_flank <- utr3_by_gene_flank[,c("gene_id")]
utr3_by_tx <- GenomicFeatures::threeUTRsByTranscript(txdb, use.names=FALSE)
all_utr3 <- unlist(utr3_by_tx, use.names=FALSE)
mcols(all_utr3)$tx_id <- rep(as.integer(names(utr3_by_tx)), lengths(utr3_by_tx))
tx2gene <- mcols(transcripts(txdb, columns=c("tx_id", "tx_name", "gene_id")))
tx2gene$gene_id <- as.character(tx2gene$gene_id)
m <- match(mcols(all_utr3)$tx_id, tx2gene$tx_id)
mcols(all_utr3) <- cbind(mcols(all_utr3), tx2gene[m, -1L, drop=FALSE])
m <- match(unique(all_utr3),all_utr3)
all_utr3_unique <- all_utr3[m]
utr5_by_tx <- GenomicFeatures::fiveUTRsByTranscript(txdb, use.names=FALSE)
all_utr5 <- unlist(utr5_by_tx, use.names=FALSE)
mcols(all_utr5)$tx_id <- rep(as.integer(names(utr5_by_tx)), lengths(utr5_by_tx))
tx2gene <- mcols(transcripts(txdb, columns=c("tx_id", "tx_name", "gene_id")))
tx2gene$gene_id <- as.character(tx2gene$gene_id)
m <- match(mcols(all_utr5)$tx_id, tx2gene$tx_id)
mcols(all_utr5) <- cbind(mcols(all_utr5), tx2gene[m, -1L, drop=FALSE])
m <- match(unique(all_utr5),all_utr5)
all_utr5_unique <- all_utr5[m]
# Reading all bam files
message("reading WT RNA-seq bam files... ")
if (ispairedendread){
ispairedendreadtext = "paired-end-read"
}
myWTbams <- lapply(myWTpaths, function (i){
if (ispairedendread){
myparam <- ScanBamParam(flag=scanBamFlag(isProperPair=TRUE,
isDuplicate=NA,
isSecondaryAlignment=FALSE))
retvalpairs <- GenomicAlignments::readGAlignmentPairs(i,
use.names = TRUE,
strandMode = 1,
param = myparam)
retval <- GenomicAlignments::granges(retvalpairs)
if (ReverseBamFileStrand){
retval <- invertStrand(retval[GenomicRanges::seqnames(retval) %in% GenomeInfoDb::seqlevels(genes_GRangelist)[1:chromosomecount], ])
} else {
retval <- retval[GenomicRanges::seqnames(retval) %in% GenomeInfoDb::seqlevels(genes_GRangelist)[1:chromosomecount], ]
}
} else {
myparam <- ScanBamParam(flag=scanBamFlag(isDuplicate=NA,
isSecondaryAlignment=FALSE))
if (ReverseBamFileStrand){
retval <- invertStrand(GenomicAlignments::readGAlignments(i,
use.names = FALSE,
param = myparam))
} else {
retval <- GenomicAlignments::readGAlignments(i,
use.names = FALSE,
param = myparam)
}
}
message(paste0("...imported ",ispairedendreadtext," WT bam file ",i))
return(retval)
})
message("OK!")
message("reading Treatment RNA-seq bam files... ")
myTreatmentbams <- lapply(myTreatmentpaths, function (i){
if (ispairedendread){
myparam <- ScanBamParam(flag=scanBamFlag(isProperPair=TRUE,
isDuplicate=NA,
isSecondaryAlignment=FALSE))
retvalpairs <- GenomicAlignments::readGAlignmentPairs(i,
use.names = TRUE,
strandMode = 1,
param = myparam)
retval <- GenomicAlignments::granges(retvalpairs)
retval <- invertStrand(retval[GenomicRanges::seqnames(retval) %in% GenomeInfoDb::seqlevels(genes_GRangelist)[1:chromosomecount], ])
} else {
myparam <- ScanBamParam(flag=scanBamFlag(isDuplicate=NA,
isSecondaryAlignment=FALSE))
retval <- invertStrand(GenomicAlignments::readGAlignments(i,
use.names = FALSE,
param = myparam))
}
message(paste0("...imported ",ispairedendreadtext," Treatment bam file ",i))
return(retval)
})
message("OK!")
message("reading the Parclip XL-reads bam file... ")
# READE PARCLIP
myPARCLIPbam <- GenomicAlignments::readGAlignments(myPARCLIPpath, use.names = TRUE)
myPARCLIPbam <- myPARCLIPbam[GenomicRanges::seqnames(myPARCLIPbam) %in% GenomeInfoDb::seqlevels(genes_GRangelist)[1:chromosomecount], ]
message("OK!")
message("mapping RNA-seq reads to gene annotation regions...")
#Gene
#minoverlapOnGenes=round(overlapcoef*readlength)
for (repID in 1:length(myWTbams)){
mcols(genes_GRangelist)[[paste0("WTgene",repID)]] <- GenomicRanges::countOverlaps(genes_GRangelist, myWTbams[[repID]], type = "any", maxgap = TargetTolerance, ignore.strand = FALSE)
}
for (repID in 1:length(myTreatmentbams)){
mcols(genes_GRangelist)[[paste0("Treatmentgene",repID)]] <- GenomicRanges::countOverlaps(genes_GRangelist, myTreatmentbams[[repID]], type = "any", maxgap = TargetTolerance, ignore.strand = FALSE)
}
mcols(genes_GRangelist)[["PARCLIPgene"]] <- GenomicRanges::countOverlaps(genes_GRangelist, myPARCLIPbam, type = "any", ignore.strand = ignoreParclipStrand)
genes_df <- as.data.frame(genes_GRangelist)
setDT(genes_df)
#Exon
for (repID in 1:length(myWTbams)){
mcols(exonsall)[[paste0("WTexon",repID)]] <- GenomicRanges::countOverlaps(exonsall, myWTbams[[repID]], type = "any", minoverlap = minoverlapOnExons, ignore.strand = FALSE)
}
for (repID in 1:length(myTreatmentbams)){
mcols(exonsall)[[paste0("Treatmentexon",repID)]] <- GenomicRanges::countOverlaps(exonsall, myTreatmentbams[[repID]], type = "any", minoverlap = minoverlapOnExons, ignore.strand = FALSE)
}
mcols(exonsall)[["PARCLIPexon"]] <- GenomicRanges::countOverlaps(exonsall, myPARCLIPbam, type = "any", ignore.strand = ignoreParclipStrand)
exonsalldf <- as.data.frame(exonsall)
setDT(exonsalldf)
exons_gene <- exonsalldf[, lapply(.SD,sum), .SDcols = which(grepl("WTexon|Treatmentexon|PARCLIPexon|width",colnames(exonsalldf))), by = "gene_id"]
colnames(exons_gene)[which(colnames(exons_gene)=="width")] <- "exonwidth"
#Intron
for (repID in 1:length(myWTbams)){
mcols(intronsfinalall)[[paste0("WTintron",repID)]] <- GenomicRanges::countOverlaps(intronsfinalall, myWTbams[[repID]], type = "any", minoverlap = minoverlapOnIntrons, ignore.strand = FALSE)
}
for (repID in 1:length(myTreatmentbams)){
mcols(intronsfinalall)[[paste0("Treatmentintron",repID)]] <- GenomicRanges::countOverlaps(intronsfinalall, myTreatmentbams[[repID]], type = "any", minoverlap = minoverlapOnIntrons, ignore.strand = FALSE)
}
mcols(intronsfinalall)[["PARCLIPintron"]] <- GenomicRanges::countOverlaps(intronsfinalall, myPARCLIPbam, type = "any", ignore.strand = ignoreParclipStrand)
intronsfinalalldf <- as.data.frame(intronsfinalall)
setDT(intronsfinalalldf)
introns_gene <- intronsfinalalldf[, lapply(.SD,sum), .SDcols = which(grepl("WTintron|Treatmentintron|PARCLIPintron|width",colnames(intronsfinalalldf))), by = "gene_id"]
colnames(introns_gene)[which(colnames(introns_gene)=="width")] <- "intronwidth"
# Extension
minoverlapOnExtensions=round(overlapcoef*readlength)
for (repID in 1:length(myWTbams)){
mcols(utr3_by_gene_flank)[[paste0("WTExtension",repID)]] <- GenomicRanges::countOverlaps(utr3_by_gene_flank, myWTbams[[repID]], type = "any", minoverlap = minoverlapOnExtensions, ignore.strand = FALSE)
}
for (repID in 1:length(myTreatmentbams)){
mcols(utr3_by_gene_flank)[[paste0("TreatmentExtension",repID)]] <- GenomicRanges::countOverlaps(utr3_by_gene_flank, myTreatmentbams[[repID]], type = "any", minoverlap = minoverlapOnExtensions, ignore.strand = FALSE)
}
utr3_by_gene_flank_df <- as.data.frame(utr3_by_gene_flank)
colnames(utr3_by_gene_flank_df)[which(colnames(utr3_by_gene_flank_df)=="width")] <- "Extensionwidth"
setDT(utr3_by_gene_flank_df)
#CDS
mcols(cds_unlist)[["PARCLIPCDS"]] <- GenomicRanges::countOverlaps(cds_unlist, myPARCLIPbam, type = "any", ignore.strand = ignoreParclipStrand)
cds_unlistdf <- as.data.frame(cds_unlist, row.names = NULL)
setDT(cds_unlistdf)
cds_gene <- cds_unlistdf[, lapply(.SD,sum), .SDcols = which(grepl("PARCLIPCDS",colnames(cds_unlistdf))), by = "gene_id"]
#3UTR
mcols(all_utr3_unique)[["PARCLIP3UTR"]] <- GenomicRanges::countOverlaps(all_utr3_unique, myPARCLIPbam, type = "any", maxgap = TargetTolerance, ignore.strand = ignoreParclipStrand)
all_utr3_uniquedf <- as.data.frame(all_utr3_unique)
setDT(all_utr3_uniquedf)
utr3_gene <- all_utr3_uniquedf[, lapply(.SD,sum), .SDcols = which(grepl("PARCLIP3UTR",colnames(all_utr3_uniquedf))), by = "gene_id"]
#5UTR
mcols(all_utr5_unique)[["PARCLIP5UTR"]] <- GenomicRanges::countOverlaps(all_utr5_unique, myPARCLIPbam, type = "any", maxgap = TargetTolerance, ignore.strand = ignoreParclipStrand)
all_utr5_uniquedf <- as.data.frame(all_utr5_unique)
setDT(all_utr5_uniquedf)
utr5_gene <- all_utr5_uniquedf[, lapply(.SD,sum), .SDcols = which(grepl("PARCLIP5UTR",colnames(all_utr5_uniquedf))), by = "gene_id"]
# UPTO HERE NOW PARCLIP
message("integrating information to a preliminary master table: MasterTableOriginal..")
# Make MasterTable
MasterTable0 <- base::merge(genes_df,exons_gene, by = "gene_id", all.x = TRUE)
MasterTable1 <- base::merge(MasterTable0,introns_gene, by = "gene_id", all.x = TRUE)
MasterTable1cds <- base::merge(MasterTable1,cds_gene, by = "gene_id", all.x = TRUE)
MasterTable2 <- base::merge(MasterTable1cds,utr3_gene, by = "gene_id", all.x = TRUE)
MasterTable3 <- base::merge(MasterTable2,utr5_gene, by = "gene_id", all.x = TRUE)
MasterTableOriginal <- base::merge(MasterTable3,utr3_by_gene_flank_df[,c("gene_id","Extensionwidth",colnames(utr3_by_gene_flank_df)[which(grepl("WTExtension|TreatmentExtension",colnames(utr3_by_gene_flank_df)))]),with=FALSE], by = "gene_id", all.x = TRUE)
setDT(MasterTableOriginal)
MasterTableOriginal
#numericcolnames <- colnames(MasterTableOriginal)[-which(colnames(MasterTableOriginal) %in% c("gene_id","seqnames","start","end","width","strand","tx_len","gene_name","gene_type"))]
#for(j in (numericcolnames)){data.table::set(MasterTableOriginal, i = which(is.na(MasterTableOriginal[[j]])), j = j, value = 0)}
message("removing all RNA genes...")
MasterTableOriginal <- MasterTableOriginal[!grepl("^RPL|^RPS|^EEEF1A|^EEF1A|^LENG7",gene_name) & !grepl("RNA$",gene_type) ,]
if (FilterPseudogenes) {
message("If the GTF had a gene_type column, removing all pseudogenes...")
MasterTableOriginal <- MasterTableOriginal[!grepl("pseudogene$",gene_type), ]
}
if (FilterAntisense){
message("If the GTF had a gene_type column, removing all antisense genes...")
MasterTableOriginal <- MasterTableOriginal[!grepl("antisense$",gene_type), ]
}
message("OK!")
MasterTable <- MasterTableOriginal
# GET GENE TPM READY
if (!RNAseqLengthNormalize){
message("Calculating TPM for gene/exon/intron annotations")
# GET EXTENSION TPM READY
extensioncolnames <- colnames(MasterTable)[which(grepl("WTExtension|TreatmentExtension",colnames(MasterTable)))]
for (k in extensioncolnames) {data.table::set(x=MasterTable, j=k, value = (10^6/sum(MasterTable[[gsub("Extension","gene",k)]]/MasterTable[["Extensionwidth"]],na.rm = TRUE))*MasterTable[[k]]/MasterTable[["Extensionwidth"]])}
# GET GENE TPM READY
genecolnames <- colnames(MasterTable)[which(grepl("WTgene|Treatmentgene",colnames(MasterTable)))]
for (k in genecolnames) {data.table::set(x=MasterTable, j=k, value = (10^6/sum(MasterTable[[k]]/MasterTable[["width"]],na.rm = TRUE))*MasterTable[[k]]/MasterTable[["width"]])}
#for(j in (genecolnames)){data.table::set(MasterTable, i = which(is.nan(MasterTable[[j]])), j = j, value = 0)}
# GET EXON TPM READY
exoncolnames <- colnames(MasterTable)[which(grepl("WTexon|Treatmentexon",colnames(MasterTable)))]
for (k in exoncolnames) {data.table::set(x=MasterTable, j=k, value = (10^6/sum(MasterTable[[k]]/MasterTable[["exonwidth"]],na.rm = TRUE))*MasterTable[[k]]/MasterTable[["exonwidth"]])}
# GET INTRON TPM READY
introncolnames <- colnames(MasterTable)[which(grepl("WTintron|Treatmentintron",colnames(MasterTable)))]
for (k in introncolnames) {data.table::set(x=MasterTable, j=k, value = (10^6/sum(MasterTable[[k]]/MasterTable[["intronwidth"]],na.rm = TRUE))*MasterTable[[k]]/MasterTable[["intronwidth"]])}
} else {
message("Calculating RPKM for gene/exon/intron annotations")
# GET EXTENSION RPKM READY
extensioncolnames <- colnames(MasterTable)[which(grepl("WTExtension|TreatmentExtension",colnames(MasterTable)))]
for (k in extensioncolnames) {data.table::set(x=MasterTable, j=k, value = (10^9/sum(MasterTable[[gsub("Extension","gene",k)]]/1,na.rm = TRUE))*MasterTable[[k]]/MasterTable[["Extensionwidth"]])}
# GET GENE RPKM READY
genecolnames <- colnames(MasterTable)[which(grepl("WTgene|Treatmentgene",colnames(MasterTable)))]
for (k in genecolnames) {data.table::set(x=MasterTable, j=k, value = (10^9/sum(MasterTable[[k]]/1,na.rm = TRUE))*MasterTable[[k]]/MasterTable[["width"]])}
#for(j in (genecolnames)){data.table::set(MasterTable, i = which(is.nan(MasterTable[[j]])), j = j, value = 0)}
# GET EXON RPKM READY
exoncolnames <- colnames(MasterTable)[which(grepl("WTexon|Treatmentexon",colnames(MasterTable)))]
for (k in exoncolnames) {data.table::set(x=MasterTable, j=k, value = (10^9/sum(MasterTable[[k]]/1,na.rm = TRUE))*MasterTable[[k]]/MasterTable[["exonwidth"]])}
# GET INTRON RPKM READY
introncolnames <- colnames(MasterTable)[which(grepl("WTintron|Treatmentintron",colnames(MasterTable)))]
for (k in introncolnames) {data.table::set(x=MasterTable, j=k, value = (10^9/sum(MasterTable[[k]]/1,na.rm = TRUE))*MasterTable[[k]]/MasterTable[["intronwidth"]])}
}
message("averaging across ",length(myWTpaths)," WT replicates and ",length(myTreatmentpaths)," Treatment replicates... computing gene, exonic, intronic, and downstream extension expressions... taking log2 differentials between WT and Treatment expressions... ")
# AVERAGING EXPRESSIONS
WTgenecolnames <- colnames(MasterTable)[which(grepl("WTgene",colnames(MasterTable)))]
MasterTable[, WTTPM := rowMeans(MasterTable[,WTgenecolnames,with=FALSE],na.rm = TRUE)]
Treatmentgenecolnames <- colnames(MasterTable)[which(grepl("Treatmentgene",colnames(MasterTable)))]
MasterTable[, TreatmentTPM := rowMeans(MasterTable[,Treatmentgenecolnames,with=FALSE],na.rm = TRUE)]
#AVERAGING EXTENSION EXPRESSION
WTextensioncolnames <- colnames(MasterTable)[which(grepl("WTExtension",colnames(MasterTable)))]
MasterTable[, WTExtensionTPM := rowMeans(MasterTable[,WTextensioncolnames,with=FALSE],na.rm = TRUE)]
Treatmentextensioncolnames <- colnames(MasterTable)[which(grepl("TreatmentExtension",colnames(MasterTable)))]
MasterTable[, TreatmentExtensionTPM := rowMeans(MasterTable[,Treatmentextensioncolnames,with=FALSE],na.rm = TRUE)]
# AVERAGING RATIO OF EXTENSION TO GENE EXPRESSION
MasterTable[, WTExtensionRatio := (MasterTable[["WTExtensionTPM"]]/1)/(MasterTable[["WTTPM"]]/1)]
MasterTable[, TreatmentExtensionRatio := (MasterTable[["TreatmentExtensionTPM"]]/1)/(MasterTable[["TreatmentTPM"]]/1)]
#=========================
#AVERAGING EXON
WTexoncolnames <- colnames(MasterTable)[which(grepl("WTexon",colnames(MasterTable)))]
MasterTable[, WTexonmean := rowMeans(MasterTable[,WTexoncolnames,with=FALSE],na.rm = TRUE)]
Treatmentexoncolnames <- colnames(MasterTable)[which(grepl("Treatmentexon",colnames(MasterTable)))]
MasterTable[, Treatmentexonmean := rowMeans(MasterTable[,Treatmentexoncolnames,with=FALSE],na.rm = TRUE)]
#AVERAGING INTRON
WTintroncolnames <- colnames(MasterTable)[which(grepl("WTintron",colnames(MasterTable)))]
MasterTable[, WTintronmean := rowMeans(MasterTable[,WTintroncolnames,with=FALSE],na.rm = TRUE)]
Treatmentintroncolnames <- colnames(MasterTable)[which(grepl("Treatmentintron",colnames(MasterTable)))]
MasterTable[, Treatmentintronmean := rowMeans(MasterTable[,Treatmentintroncolnames,with=FALSE],na.rm = TRUE)]
#=========================
MasterTableReplicates <- MasterTable
MasterTable <- MasterTable[,c("seqnames","start","end","gene_id","gene_name","strand","gene_type","tx_len","width","exonwidth","intronwidth","Extensionwidth","WTTPM","TreatmentTPM","WTexonmean","Treatmentexonmean","WTintronmean","Treatmentintronmean","WTExtensionTPM","TreatmentExtensionTPM","WTExtensionRatio","TreatmentExtensionRatio","PARCLIPgene","PARCLIP5UTR","PARCLIPCDS","PARCLIPintron","PARCLIP3UTR")]
MasterTable[, log2fC := log2((MasterTable[["TreatmentTPM"]]+1)/(MasterTable[["WTTPM"]]+1))]
MasterTable[, log2fCexon := log2((MasterTable[["Treatmentexonmean"]]+1)/(MasterTable[["WTexonmean"]]+1))]
MasterTable[, log2fCintron := log2((MasterTable[["Treatmentintronmean"]]+1)/(MasterTable[["WTintronmean"]]+1))]
MasterTable[, log2fCextension := log2((MasterTable[["TreatmentExtensionRatio"]]+0.05)/(MasterTable[["WTExtensionRatio"]]+0.05))]
message("DONE! ... with part 1")
# return Master Table
return(list(MasterTable, MasterTableReplicates))
} else {
## //INPUT CHECKING
## .................
# filter, subset and extract the columns for plotting and calculations
MasterTable <- MasterTable[WTTPM >= absminTPM &
TreatmentTPM >= absminTPM &
tx_len >= minTxSize &
(WTTPM <= maxTPM & TreatmentTPM <= maxTPM) &
(WTTPM >= minTPM | TreatmentTPM >= minTPM) ]
message(paste0("filtered MasterTable for transcript length of at least ",minTxSize,"nt."))
message(paste0("filtered MasterTable for RPKM of at least ",absminTPM," in both samples and at least ",minTPM," in either sample."))
message(paste0("filtered MasterTable for RPKM of at most ",maxTPM," in both samples."))
if (plotByColumn == "log2fCexon"){
MasterTable <- MasterTable[WTexonmean >= absminexon &
Treatmentexonmean >= absminexon &
exonwidth >= minExonSize &
(WTexonmean >= minexon | Treatmentexonmean >= minexon) ]
message(paste0("additionally filtered MasterTable for exon length of at least ",minExonSize,"nt."))
message(paste0("additionally filtered MasterTable for average exonic RPKM of at least ",absminexon, " in both samples and at least ",minintron," in either sample."))
}
if (plotByColumn == "log2fCintron"){
MasterTable <- MasterTable[WTintronmean >= absminintron &
Treatmentintronmean >= absminintron &
intronwidth >= minIntronSize &
(WTintronmean >= minintron | Treatmentintronmean >= minintron) ]
message(paste0("additionally filtered MasterTable for intron length of at least ",minIntronSize,"nt."))
message(paste0("additionally filtered MasterTable for average intronic RPKM of at least ",absminintron, " in both samples and at least ",minintron," in either sample."))
}
if (plotByColumn == "log2fCextension"){
MasterTable <- MasterTable[WTExtensionRatio >= absminExtensionRatio & TreatmentExtensionRatio >= absminExtensionRatio &
(WTExtensionRatio >= minExtensionRatio | TreatmentExtensionRatio >= minExtensionRatio)]
message(paste0("additionally filtered MasterTable for downstream expression of at least ",absminExtensionRatio," of corresponding gene expression in both samples and at least ",minExtensionRatio," in either sample."))
}
# RNA SEQ LENGTH NORMALIZATION
# PARCLIP BINNING
#in the next version, normalize the binning by WTTPM, WTexonmean, and WTintronmean
if (exprNormalization){
if (!PARCLIPLengthNormalize){
message(paste0("gene binning of: ",plotByColumn," for target region: ",binColumn,", using log2 [ (10^6*XL/sum(XL) / (Gene Expression in WT) ] gene distribution..."))
MasterTable[, target := log2(10^6*(MasterTable[[binColumn]]/sum(MasterTable[[binColumn]],na.rm = TRUE))/(MasterTable[["WTTPM"]]+1))]
} else {
message(paste0("gene binning of: ",plotByColumn," for target region: ",binColumn,", using log2 [ (10^9*XL/sum(XL) / (Length-Normalized Gene Expression in WT) ] gene distribution..."))
MasterTable[, target := log2(10^9*((MasterTable[[binColumn]]/MasterTable[["width"]])/sum(MasterTable[[binColumn]]/MasterTable[["width"]],na.rm = TRUE))/(MasterTable[["WTTPM"]]+1))]
}
} else {
if (!PARCLIPLengthNormalize){
message(paste0("gene binning of: ",plotByColumn," for target region: ",binColumn,", using log2 [ (10^6*XL/sum(XL) ] gene distribution..."))
MasterTable[, target := log2(10^6*(MasterTable[[binColumn]]/sum(MasterTable[[binColumn]],na.rm = TRUE)))]
} else {
message(paste0("gene binning of: ",plotByColumn," for target region: ",binColumn,", using log2 [ (10^9*(XL/GeneLength)/sum((XL/GeneLength)) ] gene distribution..."))
MasterTable[, target := log2(10^9*((MasterTable[[binColumn]]/MasterTable[["width"]])/sum(MasterTable[[binColumn]]/MasterTable[["width"]],na.rm = TRUE))/(1+0))]
}
}
targetmean <- mean(unlist(MasterTable[is.finite(MasterTable[["target"]]),"target",with=FALSE]),na.rm = TRUE)
targetsd <- sd(unlist(MasterTable[is.finite(MasterTable[["target"]]),"target",with=FALSE]),na.rm = TRUE)
q1 <- targetmean + targetsd
q2 <- targetmean
q3 <- targetmean - targetsd
MasterTable[, binning := binNames[1]]
MasterTable[is.finite(target),"binning"] <- binNames[2]
MasterTable[target > q3 & target <= q2 ,"binning"] <- binNames[3]
MasterTable[target > q2 & target <= q1 ,"binning"] <- binNames[4]
MasterTable[target > q1,"binning"] <- binNames[5]
message("OK!")
if (!includeBin0){
MasterTable <- MasterTable[binning != "bin0",]
}
# subset the master table
MT <- MasterTable[, c("gene_name","gene_type","log2fC","log2fCexon","log2fCintron","log2fCextension","target","binning"), with=FALSE]
# helper histogram
if (seehistogram == TRUE) {
print(hist(unlist(MT[is.finite(MT[["target"]]),"target",with=FALSE]),
breaks = histBreaks,main=paste0(binColumn," target distribution on genes")))
}
## //CREATE SUMMARY DATA
## ......................
plot_colors <- c("black", rev(brewer.pal(length(binNames[-1]), "Spectral")))
ggtitle = paste(AnalysisName,"\nCDP plotted by: ",plotByColumn," binned by: ", binColumn, sep = "")
# select the data frame
DF <- data.frame(MT[,c(plotByColumn,"target","binning"), with=FALSE])
# calculate medians
DFmed <- data.frame(bin = binNames,
x = unlist(lapply(binNames,function(i){signif(median(DF[DF[,"binning"] == i,][,plotByColumn]),digits = 2)})),
y = rep(0.01,length(binNames)))
message("...generated median table for all the bins.")
# calculate legend
binRange <- lapply(binNames, function(i){
imin <- signif(min(DF[DF[,"binning"] == i,][,"target"],na.rm = TRUE),2)
imax <- signif(max(DF[DF[,"binning"] == i,][,"target"],na.rm = TRUE),2)
return(paste(imin," , ",imax,sep = ""))})
DFks <- data.frame(bin = binNames,
binRange = unlist(binRange),
n = as.character(unlist(lapply(binNames, function(i){nrow(DF[DF[,"binning"] == i,])}))),
m = DFmed$x,
x = c(unlist(lapply(binNames,function(i){retval=NA;if ((!includeBin0) | (dim(DF[DF[,"binning"] == binNames[1],])[1]==0)) {return(NA)} else {retval=format.pval(
ks.test(DF[DF[,"binning"] == binNames[1],][,plotByColumn],DF[DF[,"binning"] == i,][,plotByColumn],
alternative = "two.sided")$p.val,digits = 3);return(retval)}}))))
message("...calculated p-values using ks.test")
## //PLOTTING THE RESULTS
## .......................
p<-ggplot(DF, aes_string(x = plotByColumn)) +
stat_ecdf(aes(colour =binning), geom = "step", size = lineSize) +
xlab(label = xlab) +
ylab(label = ylab) +
ggtitle(label = ggtitle) +
theme_bw() +
scale_x_continuous(limits = limitsX) +
scale_y_continuous(expand = c(0.01,0)) +
scale_color_manual(values = plot_colors, name = paste(legendTitle[1],"; ",legendTitle[2],"; ",legendTitle[3],"; ",legendTitle[4],sep = ""),
labels = paste(DFks[,2],"; ",DFks[,3],"; ",DFks[,4],"; ", DFks[,5], sep = "")) +
geom_point(data = DFmed, aes(x = x, y = y, colour = factor(bin)), size = pointSize) +
theme(plot.title = element_text(size = ggTitleSize, family = fontFamily, hjust = 0.5),
panel.grid = element_blank(),
panel.border = element_rect(colour = "black", size = panelBorderSize),
legend.position = legendPosition,
legend.title = element_text(size = legendTextSize),
legend.background = element_blank(),
legend.key.size = unit(legendSpacing, 'lines'),
legend.text = element_text(size = legendTextSize, family = fontFamily),
axis.title.x = element_text(size = axisTitleSize, family = fontFamily,vjust = -1),
axis.text.x = element_text(size = axisTextSize, family = fontFamily, face = "plain"),
axis.title.y = element_text(size = axisTitleSize, family = fontFamily,vjust = 2),
axis.text.y = element_text(size = axisTextSize, family = fontFamily, face = "plain"),
plot.margin = margin(2,2,2,2,"cm"),
aspect.ratio = 1)
# plot.margin = margin(1,0.25,1,0.25,"cm")
if (returnAll == TRUE) {
dataList <- list(MasterTable, MT, DFmed, DFks, p, plot_colors)
names(dataList) <- c("AveragedValues", "binnedTable", "MedianTable", "Kolmogorov-SmirnovTable","ggPlot","plotColors")
return(dataList)
} else {
return(p)
}
}
message("DONE!")
}