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atacQC_v2.R
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atacQC_v2.R
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#!/usr/bin/env Rscript
args <- commandArgs(trailingOnly = T)
# check for required argument
if (length(args)==0) {
print(" Usage = Rscript atacQC.R < human, mouse or 'path to gtf annotation' >")
stop("Missing gtf annotation path !!! \n", call.=FALSE)
}
library(progress)
pb <- progress_bar$new(total = 100)
for (i in 1:20) {
pb$tick()
Sys.sleep(1 / 10)
}
#-----------------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------------
# fragSize - Distributions
suppressPackageStartupMessages(library(ATACseqQC))
bamfiles <- list.files(pattern = ".bam$")
bamfile.labels <- gsub(".DEDUP.bam", "", basename(bamfiles))
for (i in 1:length(bamfiles)) {
png(filename = paste0(strsplit(x = bamfiles[i],
split = "\\.DEDUP.bam"[[1]]),".fragSize" ,".png"),
width = 1080, height = 1080, res = 155)
fragSizeDist(bamfiles[i], bamfile.labels[i])
dev.off()
}
for (i in 1:30) {
pb$tick()
Sys.sleep(1 / 100)
}
#-----------------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------------
# Peak Distributions + Peak Annotation
suppressPackageStartupMessages(library(GenomicFeatures))
suppressPackageStartupMessages(library(ChIPseeker))
suppressPackageStartupMessages(library(clusterProfiler))
for (i in 1:30) {
pb$tick()
Sys.sleep(1 / 100)
}
#-----------------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------------
# import peak files as list
files <- list.files(path = "../MACS2_peaks", pattern = ".narrowPeak$", full.names = T)
files <- as.list(files[1:length(files)])
for (i in 1:length(files)) {
names(files[[i]]) <- gsub(pattern = ".narrowPeak",
replacement = "", basename(files[[i]]))
}
if (args[1]=="mouse") {
gtf.path <- "/workdir/genomes/Mus_musculus/mm10/ENSEMBL/Mus_musculus.GRCm38.96.gtf"
org <- "Mus musculus"
} else if (args[1]=="human"){
gtf.path <- "/workdir/genomes/Homo_sapiens/hg38/ENSEMBL/Homo_sapiens.GRCh38.96.gtf"
org <- "Homo sapiens"
} else {
gtf.path <- args[1]
org <- "NA"
}
for (i in 1:20) {
pb$tick()
Sys.sleep(1 / 100)
}
txdb <- makeTxDbFromGFF(gtf.path,
format = "gtf", organism = org)
#-----------------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------------
# import peak files as list
files <- list.files(path = "../MACS2_peaks", pattern = ".narrowPeak$", full.names = T)
files <- as.list(files[1:length(files)])
for (i in 1:length(files)) {
names(files[[i]]) <- gsub(pattern = ".narrowPeak",
replacement = "", basename(files[[i]]))
}
#-----------------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------------
promoter <- getPromoters(TxDb=txdb, upstream=3000, downstream=3000)
for (i in 1:length(files)) {
print(paste0("Processing -- ", names(files[[i]])))
peak <- readPeakFile(files[[i]])
tagMatrix <- getTagMatrix(peak, windows=promoter)
png(filename = paste0(basename(files[[i]]),".Distribution.png"),
width = 720, height = 640)
c1 <- plotAvgProf(tagMatrix, xlim=c(-3000, 3000),
xlab="Genomic Region (5'->3')",
ylab = paste0("Read Count Frequency - ",
basename(files[[i]])))
print(c1)
dev.off()
peakAnno <- annotatePeak(peak, TxDb=txdb)
png(filename = paste0(basename(files[[i]]),".Annotated.png"),
width = 720, height = 320)
c2 <- plotAnnoBar(peakAnno, title = basename(files[[i]]))
print(c2)
dev.off()
write.table(c2$data, file = paste0(c2$labels$title, "__percent__annot__log.txt"), sep = "\t")
}
#-----------------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------------
# Calculate TSSE scores
txs <- transcripts(txdb)
bamsList = list()
for (i in 1:length(bamfile.labels)) {
bamsList[[i]] <- readBamFile(bamfiles[i], bigFile = T)
names(bamsList)[[i]] <- bamfile.labels[i]
}
tsseScores = lapply(bamsList, function(x){
tsse = TSSEscore(obj = x, txs = txs)
score = tsse$TSSEscore
return(score)
})
tsseScores.df = as.data.frame(round(unlist(tsseScores), 2))
colnames(tsseScores.df) = "value"
tsseScores.df$labels = rownames(tsseScores.df)
saveRDS(tsseScores, "tsseScores.RDS")
library(ggplot2)
png("TSSE_scores.png", width = 1080, height = 1080, res = 100)
ggplot(data = tsseScores.df, aes(x = labels, y = value )) + geom_bar(stat = "identity") +
geom_text(aes(label=value), vjust=1.6, color="white", size=3.5) + ggtitle("Transcription Start Site (TSS) Enrichment Scores") +
xlab("Sample") + ylab("TSS Score") + scale_y_continuous() + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
dev.off()
system("mkdir atacQC.out")
system("mv *.png atacQC.out")
system("mv *_peaks.narrowPeak__percent__annot__log.txt tsseScores.RDS atacQC.out")