Mercurial > repos > iuc > scater_plot_dist_scatter
view scater-create-qcmetric-ready-sce.R @ 1:2e41b35b5bdd draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scater commit 61f3899168453092fd25691cf31871a3a350fd3b"
author | iuc |
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date | Tue, 03 Sep 2019 14:25:32 -0400 |
parents | 4887c4c69847 |
children | 81e5bdff4853 |
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#!/usr/bin/env Rscript #Creates a SingleCellExperiment object, which scater's calculateQCMetrics already applied library(optparse) library(workflowscriptscommon) library(scater) library(LoomExperiment) # parse options #SCE-specific options option_list = list( make_option( c("-a", "--counts"), action = "store", default = NA, type = 'character', help = "A tab-delimited expression matrix. The first column of all files is assumed to be feature names and the first row is assumed to be sample names." ), make_option( c("-r", "--row-data"), action = "store", default = NULL, type = 'character', help = "Path to TSV (tab-delimited) format file describing the features. Row names from the expression matrix (-a), if present, become the row names of the SingleCellExperiment." ), make_option( c("-c", "--col-data"), action = "store", default = NULL, type = 'character', help = "Path to TSV format file describing the samples (annotation). The number of rows (samples) must equal the number of columns in the expression matrix." ), #The scater-specific options make_option( c("--assay-name"), action = "store", default = 'counts', type = 'character', help= "String specifying the name of the 'assay' of the 'object' that should be used to define expression." ), make_option( c("-f", "--mt-controls"), action = "store", default = NULL, type = 'character', help = "Path to file containing a list of the mitochondrial control genes" ), make_option( c("-p", "--ercc-controls"), action = "store", default = NULL, type = 'character', help = "Path to file containing a list of the ERCC controls" ), make_option( c("-l", "--cell-controls"), action = "store", default = NULL, type = 'character', help = "Path to file (one cell per line) to be used to derive a vector of cell (sample) names used to identify cell controls (for example, blank wells or bulk controls)." ), make_option( c("-o", "--output-loom"), action = "store", default = NA, type = 'character', help = "File name in which to store the SingleCellExperiment object in Loom format." ) ) opt <- wsc_parse_args(option_list, mandatory = c('counts', 'output_loom')) # Read the expression matrix counts <- wsc_split_string(opt$counts) reads <- read.table(counts) # Read row and column annotations rowdata <- opt$row_data if ( ! is.null(opt$row_data) ){ rowdata <- read.delim(opt$row_data) } coldata <- opt$col_data if ( ! is.null(opt$col_data) ){ coldata <- read.delim(opt$col_data) } # Now build the object assays <- list(as.matrix(reads)) names(assays) <- c(opt$assay_name) scle <- SingleCellLoomExperiment(assays = assays, colData = coldata, rowData = rowdata) # Define spikes (if supplied) #Scater options # Check feature_controls (only mitochondrial and ERCC used for now) feature_controls_list = list() if (! is.null(opt$mt_controls) && opt$mt_controls != 'NULL'){ if (! file.exists(opt$mt_controls)){ stop((paste('Supplied feature_controls file', opt$mt_controls, 'does not exist'))) } else { mt_controls <- readLines(opt$mt_controls) feature_controls_list[["MT"]] <- mt_controls } } if (! is.null(opt$ercc_controls) && opt$ercc_controls != 'NULL'){ if (! file.exists(opt$ercc_controls)){ stop((paste('Supplied feature_controls file', opt$ercc_controls, 'does not exist'))) } else { ercc_controls <- readLines(opt$ercc_controls) feature_controls_list[["ERCC"]] <- ercc_controls } } else { ercc_controls <- character() } # Check cell_controls cell_controls_list <- list() if (! is.null(opt$cell_controls) && opt$cell_controls != 'NULL'){ if (! file.exists(opt$cell_controls)){ stop((paste('Supplied feature_controls file', opt$cell_controls, 'does not exist'))) } else { cell_controls <- readLines(opt$cell_controls) cell_controls_list[["empty"]] <- cell_controls } } # calculate QCMs scle <- calculateQCMetrics(scle, exprs_values = opt$assay_name, feature_controls = feature_controls_list, cell_controls = cell_controls_list) # Output to a Loom file if (file.exists(opt$output_loom)) { file.remove(opt$output_loom) } export(scle, opt$output_loom, format='loom')