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readDGE <- function(files,path=NULL,columns=c(1,2),group=NULL,labels=NULL,...)
# Read and collate a set of count data files, each file containing counts for one library
# Created 2006. Last modified 8 Sep 2021.
{
# Create data.frame to hold sample information
x <- list()
if(is.data.frame(files)) {
x$samples <- files
if(!is.null(labels)) row.names(x$samples) <- labels
if(is.null(x$samples$files)) stop("file names not found")
x$samples$files <- as.character(x$samples$files)
} else {
files <- as.character(files)
if(is.null(labels)) labels <- removeExt(files)
x$samples <- data.frame(files=files,row.names=labels,stringsAsFactors=FALSE)
}
nfiles <- nrow(x$samples)
# Set group factor
if(!is.null(group)) x$samples$group <- group
if(is.null(x$samples$group)) x$samples$group <- rep_len(1L,nfiles)
x$samples$group <- as.factor(x$samples$group)
# Read files into a list
d <- taglist <- list()
for (fn in x$samples$files) {
if(!is.null(path)) fn <- file.path(path,fn)
d[[fn]] <- read.delim(fn,...,stringsAsFactors=FALSE)
taglist[[fn]] <- as.character(d[[fn]][,columns[1]])
if(anyDuplicated(taglist[[fn]])) {
ndup <- sum(duplicated(taglist[[fn]]))
stop("There are ",ndup," repeated row names in ",fn,". Row names must be unique.")
}
}
# Collate counts for unique tags
tags <- unique(unlist(taglist))
ntags <- length(tags)
x$counts <- matrix(0,ntags,nfiles)
dimnames(x$counts) <- list(Tags=tags,Samples=row.names(x$samples))
for (i in 1:nfiles) {
aa <- match(taglist[[i]],tags)
x$counts[aa,i] <- d[[i]][,columns[2]]
}
# Alert user if htseq-style meta genes found
MetaTags <- grep("^_",tags,value=TRUE)
if(length(MetaTags)) message("Meta tags detected: ",paste(MetaTags,collapse=", "))
# Enter library sizes and norm factors
x$samples$lib.size <- colSums(x$counts)
x$samples$norm.factors <- 1
new("DGEList",x)
}
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