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DGEList <- function(counts=matrix(0,0,0), lib.size=colSums(counts), norm.factors=rep(1,ncol(counts)), samples=NULL, group=NULL, genes=NULL, remove.zeros=FALSE)
# Construct DGEList object from components, with some checking
# Created 28 Sep 2008. Last modified 16 Nov 2020.
{
# Check whether counts is a data.frame
if(is.data.frame(counts)) {
cl <- vapply(counts,class,FUN.VALUE="")
IsNumeric <- (cl %in% c("integer","numeric"))
a <- which(!IsNumeric)
if(length(a)) {
if(length(a)==1L && a[1]==1L) {
stop(
"The count matrix is a data.frame instead of a matrix and the first column is of class ",cl[1],"\n",
" instead of being numeric. Was the first column intended to contain geneids?"
)
} else {
stop(
"The count matrix is a data.frame instead of a matrix and ",length(a)," columns are non-numeric.\n",
" Should these columns be gene annotation instead of counts?"
)
}
}
}
# Check counts
counts <- as.matrix(counts)
if( !any(typeof(counts) == c("integer","double")) ) stop("non-numeric values found in counts")
nlib <- ncol(counts)
ntags <- nrow(counts)
if(nlib>0L && is.null(colnames(counts))) colnames(counts) <- paste0("Sample",1L:nlib)
if(ntags>0L && is.null(rownames(counts))) rownames(counts) <- 1L:ntags
.isAllZero(counts) # don't really care about all-zeroes, but do want to protect against NA's, negative values.
# Check lib.size
if(is.null(lib.size)) {
lib.size <- colSums(counts)
if(min(lib.size) <= 0) warning("library size of zero detected")
} else {
if(!is.numeric(lib.size)) stop("'lib.size' must be numeric")
if(nlib != length(lib.size)) stop("length of 'lib.size' must equal number of columns in 'counts'")
minlibsize <- min(lib.size)
if(is.na(minlibsize)) stop("NA library sizes not allowed")
if(minlibsize < 0) stop("negative library sizes not permitted")
if(minlibsize == 0) {
if(any(lib.size==0 & colSums(counts)>0)) stop("library size set to zero but counts are nonzero")
warning("library size of zero detected")
}
}
# Check norm.factors
if(is.null(norm.factors)) {
norm.factors <- rep_len(1,ncol(counts))
} else {
if(!is.numeric(norm.factors)) stop("'lib.size' must be numeric")
if(!identical(nlib,length(norm.factors))) stop("Length of 'norm.factors' must equal number of columns in 'counts'")
minnf <- min(norm.factors)
if(is.na(minnf)) stop("NA norm factors not allowed")
if(minnf <= 0) stop("norm factors should be positive")
if( abs(prod(norm.factors) - 1) > 1e-6 ) warning("norm factors don't multiply to 1")
}
# Check samples
if(!is.null(samples)) {
samples <- as.data.frame(samples)
if(nlib != nrow(samples)) stop("Number of rows in 'samples' must equal number of columns in 'counts'")
}
# Get group from samples if appropriate
if(is.null(group) && !is.null(samples$group)) {
group <- samples$group
samples$group <- NULL
}
# Check group
if(is.null(group)) {
group <- rep_len(1L,nlib)
levels(group) <- "1"
class(group) <- "factor"
} else {
if(length(group) != nlib) stop("Length of 'group' must equal number of columns in 'counts'")
group <- dropEmptyLevels(group)
}
# Make data frame of sample information
sam <- data.frame(group=group,lib.size=lib.size,norm.factors=norm.factors)
if(!is.null(samples)) sam <- data.frame(sam, samples)
samples <- sam
if(anyDuplicated(colnames(counts))) {
message("Repeated column names found in count matrix")
row.names(samples) <- 1L:nlib
} else
row.names(samples) <- colnames(counts)
# Make object
x <- new("DGEList",list(counts=counts,samples=samples))
# Add data frame of gene information
if(!is.null(genes)) {
genes <- as.data.frame(genes, stringsAsFactors=FALSE)
if(nrow(genes) != ntags) stop("Counts and genes have different numbers of rows")
if(anyDuplicated(row.names(counts)))
warning("Count matrix has duplicated rownames",call.=FALSE)
else
row.names(genes) <- row.names(counts)
x$genes <- genes
}
# Remove rows with all zeros
if(remove.zeros) {
all.zeros <- rowSums(counts>0,na.rm=TRUE)==0
if(any(all.zeros)) {
x <- x[!all.zeros,]
message("Removing ",sum(all.zeros)," rows with all zero counts")
}
}
# x$offset <- expandAsMatrix(getOffset(x),dim(counts))
# x$weights <- matrix(1,ntags,nlib)
x
}
.isAllZero <- function(y)
# Check whether all counts are zero.
# Also checks and stops with an informative error message if negative, NA or infinite counts are present.
{
if (!length(y)) return(FALSE)
check.range <- range(y)
if (is.na(check.range[1])) stop("NA counts not allowed", call.=FALSE)
if (check.range[1] < 0) stop("Negative counts not allowed", call.=FALSE)
if (is.infinite(check.range[2])) stop("Infinite counts not allowed", call.=FALSE)
check.range[2]==0
}
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