R/count_filter.R

In ERSSA: Empirical RNA-seq Sample Size Analysis

#' @title Filter RNA-seq expression table
#'
#' @description
#' \code{count_filter} function filters the RNA-seq count table to remove
#' non- and low-expression genes at an defined average CPM cutoff (Default=1).
#'
#' @param count_table A RNA-seq count matrix with genes on each row and samples
#' on each column.
#' @param cutoff Any gene with average CPM below this cutoff value will be
#' filtered out.
#'
#' @return The filtered count table.
#'
#' @author Zixuan Shao, \email{Zixuanshao.zach@@gmail.com}
#'
#' @examples
#' # load simple GTeX example count table
#' # example dataset containing 1000 genes, 4 replicates
#' data(count_table.partial, package = "ERSSA")
#'
#' #filter the counts
#' count_table.filtered.partial = count_filter(count_table.partial)
#'
#' @export
#'
#' @importFrom utils write.csv


count_filter = function(count_table=NULL, cutoff=1){

    # check all required arguments supplied
    if (is.null(count_table)){
        stop('Missing required count_table argument in count_filter function')
    } else if (!(is.data.frame(count_table))){
        stop('count_table is not an expected dataframe object')
    } else if (length(unique(sapply(count_table, class)))!=1){
        stop(paste0('More than one data type detected in count table, please ',
                    'make sure count table contains only numbers and that the ',
                    'list of gene names is the dataframe index'))
    }

    cpm_table = t(t(count_table)*1000000/colSums(count_table))
    count_table_filtered = count_table[which(rowMeans(cpm_table)>cutoff),]

    return(count_table_filtered)
}