R/read.modbam2bed.R

In kasperdanielhansen/bsseq: Analyze, manage and store whole-genome methylation data

read.modbam2bed <- function(files, colData = NULL, rmZeroCov = FALSE,
                            strandCollapse = TRUE) {
    gr_list <- list()
    sampleNames <- sub("\\.bed$","",basename(files))
    if (!is.null(colData)) {
        rownames(colData) <- sampleNames
        }

    for (i in seq_along(files)) {
        data <- read.table(files[i],header = FALSE, sep="\t",
                    stringsAsFactors=FALSE, quote="")
        gr <- GRanges(seqnames = data$V1,
            ranges = IRanges(start = data$V2+1, end = data$V3))
        mcols(gr)$m <- data$V13
        mcols(gr)$cov <- data$V12 + data$V13
        mcols(gr)$filter <- data$V14
        names(gr) <- sampleNames[i]
        gr_list[[sampleNames[i]]] <- gr
        }

    overlap_gr <- Reduce(subsetByOverlaps, gr_list)

    m_cov_list <- lapply(gr_list, function(gr) {
        overlap_data <- gr[gr %over% overlap_gr]
        data.frame(m = overlap_data$m, cov = overlap_data$cov,
            filter = overlap_data$filter)})

    m <- do.call(cbind,lapply(m_cov_list,`[[`, "m"))
    cov <- do.call(cbind, lapply(m_cov_list, `[[`, "cov"))
    filter <- do.call(cbind, lapply(m_cov_list, `[[`, "filter"))

    bsseq_obj <- BSseq(M = as.matrix(m), Cov = as.matrix(cov),
                     Filtered = as.matrix(filter),
                     coef = NULL,se.coef = NULL,
                     pos = start(overlap_gr),trans = NULL,
                     parameters = NULL, pData = colData, gr = NULL,
                     chr = as.vector(seqnames(overlap_gr)),
                     sampleNames = sampleNames,rmZeroCov = rmZeroCov)

    if (strandCollapse) {
        strandCollapse(bsseq_obj)
    }

    return(bsseq_obj)
}