view 02_read_counts_tss/countsAroundTSS.R @ 1:e784d7e94374 draft default tip

Deleted selected files

## How to execute this tool
# $Rscript my_r_tool.R --input input.csv --output output.csv

# Send R errors to stderr
options(show.error.messages = F, error = function(){cat(geterrmessage(), file = stderr()); q("no", 1, F)})

# Avoid crashing Galaxy with an UTF8 error on German LC settings
loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")

options(stringAsfactors = FALSE, useFancyQuotes = FALSE)

# Check for packages requirement -----
suppressMessages(source("https://bioconductor.org/biocLite.R"))

list.of.packages <- c("GenomicRanges",
                      "Rsamtools",
                      "rtracklayer",
                      "parallel",
                      "foreach",
                      "doParallel",
                      "GenomicFeatures",
                      "Gviz",
                      "BSgenome.Hsapiens.UCSC.hg19",
                      "org.Hs.eg.db",
                      "BSgenome.Mmusculus.UCSC.mm10",
                      "org.Mm.eg.db",
                      "optparse",
                      "getopt")

new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) biocLite(new.packages)

# packages required
tmp <- suppressMessages(lapply(list.of.packages, require, quietly =T,
                               warn.conflicts = F, character.only = TRUE))
rm(tmp)


# Command line options ----
# option_list <- list(
#   make_option(c("-b", "--bamfile"), type="character", default=NULL, 
#               help="bamfile for which read counts are to be calculated around TSS", metavar="character"),
#   make_option(c("-e", "--genome"), type="character", default = NULL,
#               help="genome: hg19/ mm10", metavar="character"),
#   make_option(c("-n", "--TSSn"), type="character", default = NULL,
#               help="region upstream TSS for which the read counts are to be calculated", metavar="character"),
#   make_option(c("-p", "--TSSp"), type="character", default = NULL,
#               help="region downstream TSS for which the read counts are to be calculated", metavar="character"),
#   make_option(c("-u", "--TxDbUCSC"), type="character", default = NULL,
#               help="Transcripts database: If you already have a sqlite Transcript database for hg19/ mm10, provide it, or do not enter anything. Software will create a database to use from UCSC.", metavar="character")
# )
# 
# opt_parser <- OptionParser(option_list=option_list)
# opt <- parse_args(opt_parser)

# Take in trailing command line arguments
args <- commandArgs(trailingOnly = TRUE)
# args <- c("ENCFF027UTM.bam", "hg19", 500, 500, "transcripts_mm10_UCSC.sqlite")

# Get options using the spec as defined by the enclosed list
# Options are read from the default: commandArgs(TRUE)
option_specification = matrix(c(
  'input1', 'i1', 2, 'character',
  'input2', 'i2', 2, 'character',
  'input3', 'i3', 2, 'integer',
  'input4', 'i4', 2, 'integer',
  'input5', 'i5', 2, 'character',
  'output', 'o', 2, 'character'
), byrow=TRUE, ncol=4);

# Parse options
options = getopt(option_specification)

if (is.null(options$input1) | is.null(options$input2)){
  stop("Please provide right input parameters. See help!", call.=FALSE)
}


# opt$genome <- "mm10"
# opt$TxDbUCSC <- "transcripts_mm10_UCSC.sqlite"
# opt$bamfile <- "ENCFF027UTM.bam"
# opt$TSSn <- 500
# opt$TSSp <- 500

# Transcript database ----
txdb <- NULL
if(is.null(options$input5)){
  txdb <- makeTxDbFromUCSC(genome = options$input2, tablename="refGene")
  saveDb(txdb, file = paste("transcripts_", options$input2, "_UCSC.sqlite", sep = ""))
} else{
  txdb <- loadDb(options$input5)
}

txs <- transcripts(txdb, columns = c("gene_id", "tx_id"))
txs <- txs[sapply(split(seq_along(txs), sapply(txs$gene_id, "[", 1)),
                  function(x) x[which.max(width(txs)[x])])]

geneID <- txs$"gene_id"
genes <- as.character(geneID)


# Bamfiles and chromosomes
# bamfiles <- list.files(path = opt$bamdir, pattern = ".bam$", full.names = T)
bamfiles <- options$input1

chrs <- scanBamHeader(bamfiles)[[1]]$targets


# TSS regions for calculationg counts ----
tss <- suppressWarnings(GRanges(seqnames(txs), 
                                IRanges(start = ifelse(as.character(strand(txs)) == "+", 
                                                       start(txs), end(txs)) - as.numeric(options$input3),
                                        width = as.numeric(options$input3) + as.numeric(options$input4)), 
                                strand = strand(txs), seqlengths = chrs))


# Functions ----
mylapply <- function(...) {
  if(require(parallel) && .Platform$OS.type == "unix")
    mclapply(..., mc.cores = detectCores(), mc.preschedule = F)
  else
    lapply(...)
}

coverageForChr <- function(seqname, bamfile, chrs, fragmentSize=0, ...) {
  message(", ", seqname, appendLF=FALSE)
  shift <- round(fragmentSize/2)
  param <- ScanBamParam(what=c("pos","qwidth","strand"), 
                        which=GRanges(seqname, IRanges(1, chrs[seqname])), 
                        flag=scanBamFlag(isUnmappedQuery=FALSE))
  x <- scanBam(bamfile, ..., param=param)[[1]]
  coverage(IRanges(ifelse(x[["strand"]]=="+", x[["pos"]]+shift, 
                          x[["pos"]]+x[["qwidth"]]-shift), width=1), width=chrs[seqname])
}


countsForRegions <- function(bamfiles, regions, fragmentSize=0) {
  names(regions) <- seq_along(regions)
  chrs <- seqlengths(regions)
  DF <- do.call(cbind, lapply(bamfiles, function(bf) {
    message("counting alignments in ",basename(bf),appendLF=FALSE)
    cover <- mylapply(names(chrs), coverageForChr, bamfile=bf, chrs=chrs, fragmentSize=fragmentSize)
    names(cover) <- names(chrs)
    cover <- RleList(unlist(cover), compress=FALSE)
    vws <- Views(cover, as(regions,"RangesList"))
    vs <- unlist(viewSums(vws), use.names=FALSE)
    vs <- vs[match(names(regions), unlist(lapply(vws,names),use.names=FALSE))]
    df <- DataFrame(vs)
    colnames(df) <- sub(".bam","",basename(bf))
    message(": done")
    df
  }))
}



# Counting reads ----
cnts <- countsForRegions(bamfiles = bamfiles, regions = tss, fragmentSize = 150)
cnts <- data.frame(Genes = genes, cnts, stringsAsFactors = F, check.names = F)

# Annotating genes ----
anno <- NULL
if(options$input2 == "hg19"){
  anno <- select(org.Hs.eg.db, as.character(cnts$Genes), c("SYMBOL", "GENENAME"))
} else if (options$input2 == "mm10"){
  anno <- select(org.Mm.eg.db, as.character(cnts$Genes), c("SYMBOL", "GENENAME"))
} else {
  stop("Please provide correct reference genome. See help!", call.=FALSE)
}

cnts <- merge(anno, cnts, by.x = "ENTREZID", by.y = "Genes")

index <- which(is.na(cnts$SYMBOL))
cnts$SYMBOL[index] <- cnts$ENTREZID[index]

write.table(cnts, file = options$output, sep = "\t", row.names = F, quote = F)

sessionInfo()