R/filter.R

In kokrah/cbcbSEQ: RNAseq analysis pipeline for UMD CBCB collaborators with batch effect assessment and correction

#' Filter low expression genes, using independent filtering
#' recommended in Nature Protocols paper
#'
#' @param counts Count matrix
#' @param lib.size library sizes, if missing or sum uses the total counts per samples
#' @param thresh Minimum counts per million to determine expression
#' @param minSamples Minimum number of samples where gene is required to be expressed. This should be set to the numer of samples in the smallest group of interest.
#' @return Filtered count matrix
#' @export
filterCounts <- function(counts, lib.size = NULL,
                         thresh = 1,
                         minSamples = 2) {
    cpms <- 2^log2CPM(counts, lib.size=lib.size)$y
    keep <- rowSums(cpms > thresh) >= minSamples
    counts <- counts[keep,]
    return(counts)
}