+
−options(
+
−    show.error.messages = FALSE,
+
−    error = function() {
+
−        cat(geterrmessage(), file = stderr())
+
−        q("no", 1, FALSE)
+
−    }
+
−)
+
−loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
+
−warnings()
+
−
+
−library(optparse)
+
−library(scran)
+
−library(dynamicTreeCut)
+
−
+
−# Arguments
+
−option_list <- list(
+
−    make_option(
+
−        c("-d", "--data"),
+
−        default = NA,
+
−        type = "character",
+
−        help = "Input file that contains count values to transform"
+
−    ),
+
−    make_option(
+
−        "--cluster",
+
−        default = FALSE,
+
−        action = "store_true",
+
−        type = "logical",
+
−        help = "Whether to calculate the size factor per cluster or on all cell"
+
−    ),
+
−    make_option(
+
−        c("-m", "--method"),
+
−        default = "hclust",
+
−        type = "character",
+
−        help = "The clustering method to use for grouping cells into cluster : hclust or igraph [default : '%default' ]"
+
−    ),
+
−    make_option(
+
−        "--size",
+
−        default = 100,
+
−        type = "integer",
+
−        help = "Minimal number of cells in each cluster : hclust or igraph [default : '%default' ]"
+
−    ),
+
−    make_option(
+
−        c("-o", "--out"),
+
−        default = "res.tab",
+
−        type = "character",
+
−        help = "Output name [default : '%default' ]"
+
−    )
+
−)
+
−
+
−opt <- parse_args(OptionParser(option_list = option_list),
+
−    args = commandArgs(trailingOnly = TRUE)
+
−)
+
−
+
−
+
−data <- read.table(
+
−    opt$data,
+
−    check.names = FALSE,
+
−    header = TRUE,
+
−    row.names = 1,
+
−    sep = "\t"
+
−)
+
−
+
−## Import data as a SingleCellExperiment object
+
−sce <- SingleCellExperiment(list(counts = as.matrix(data)))
+
−
+
−if (opt$cluster) {
+
−    clusters <- quickCluster(sce, min.size = opt$size, method = opt$method)
+
−
+
−    ## Compute sum factors
+
−    sce <- computeSumFactors(sce, cluster = clusters)
+
−} else {
+
−    ## Compute sum factors
+
−    sce <- computeSumFactors(sce)
+
−}
+
−
+
−sce <- logNormCounts(sce)
+
−
+
−logcounts <- data.frame(genes = rownames(sce), round(logcounts(sce), digits = 5), check.names = FALSE)
+
−
+
−
+
−write.table(
+
−    logcounts,
+
−    opt$out,
+
−    col.names = TRUE,
+
−    row.names = FALSE,
+
−    quote = FALSE,
+
−    sep = "\t"
+
−)