Mercurial > repos > ebi-gxa > seurat_run_umap
diff scripts/seurat-scale-data.R @ 0:b9424c715a0d draft default tip
planemo upload commit 0264c359f1d638bbbbab515a3502231f679cdcf6
author | ebi-gxa |
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date | Sat, 02 Mar 2024 10:40:43 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/scripts/seurat-scale-data.R Sat Mar 02 10:40:43 2024 +0000 @@ -0,0 +1,165 @@ +#!/usr/bin/env Rscript + +# Load optparse we need to check inputs + +suppressPackageStartupMessages(require(optparse)) + +# Load common functions + +suppressPackageStartupMessages(require(workflowscriptscommon)) + +# parse options + +option_list = list( + make_option( + c("-i", "--input-object-file"), + action = "store", + default = NA, + type = 'character', + help = "File name in which a serialized R matrix object may be found." + ), + make_option( + c("--input-format"), + action = "store", + default = "seurat", + type = 'character', + help = "Either loom, seurat, anndata or singlecellexperiment for the input format to read." + ), + make_option( + c("--output-format"), + action = "store", + default = "seurat", + type = 'character', + help = "Either loom, seurat, anndata or singlecellexperiment for the output format." + ), + make_option( + c("-e", "--genes-use"), + action = "store", + default = NULL, + type = 'character', + help = "File with gene names to scale/center (one gene per line). Default is all genes in object@data." + ), + make_option( + c("-v", "--vars-to-regress"), + action = "store", + default = NULL, + type = 'character', + help = "Comma-separated list of variables to regress out (previously latent.vars in RegressOut). For example, nUMI, or percent.mito." + ), + make_option( + c("-m", "--model-use"), + action = "store", + default = 'linear', + type = 'character', + help = "Use a linear model or generalized linear model (poisson, negative binomial) for the regression. Options are 'linear' (default), 'poisson', and 'negbinom'." + ), + make_option( + c("-u", "--use-umi"), + action = "store", + default = FALSE, + type = 'logical', + help = "Regress on UMI count data. Default is FALSE for linear modeling, but automatically set to TRUE if model.use is 'negbinom' or 'poisson'." + ), + make_option( + c("-s", "--do-not-scale"), + action = "store_true", + default = FALSE, + type = 'logical', + help = "Skip the data scale." + ), + make_option( + c("-c", "--do-not-center"), + action = "store_true", + default = FALSE, + type = 'logical', + help = "Skip data centering." + ), + make_option( + c("-x", "--scale-max"), + action = "store", + default = 10, + type = 'double', + help = "Max value to return for scaled data. The default is 10. Setting this can help reduce the effects of genes that are only expressed in a very small number of cells. If regressing out latent variables and using a non-linear model, the default is 50." + ), + make_option( + c("-b", "--block-size"), + action = "store", + default = 1000, + type = 'integer', + help = "Default size for number of genes to scale at in a single computation. Increasing block.size may speed up calculations but at an additional memory cost." + ), + make_option( + c("-d", "--min-cells-to-block"), + action = "store", + default = 1000, + type = 'integer', + help = "If object contains fewer than this number of cells, don't block for scaling calculations." + ), + make_option( + c("-n", "--check-for-norm"), + action = "store", + default = TRUE, + type = 'logical', + help = "Check to see if data has been normalized, if not, output a warning (TRUE by default)." + ), + make_option( + c("-o", "--output-object-file"), + action = "store", + default = NA, + type = 'character', + help = "File name in which to store serialized R object of type 'Seurat'.'" + ) +) + +opt <- wsc_parse_args(option_list, mandatory = c('input_object_file', 'output_object_file')) + +# Check parameter values + +if ( ! file.exists(opt$input_object_file)){ + stop((paste('File', opt$input_object_file, 'does not exist'))) +} + +if (! is.null(opt$genes_use)){ + if (! file.exists(opt$genes_use)){ + stop((paste('Supplied genes file', opt$genes_use, 'does not exist'))) + }else{ + genes_use <- readLines(opt$genes_use) + } +}else{ + genes_use <- NULL +} + +# break up opt$vars_to_regress into a list if it has commas +opt$vars_to_regress <- unlist(strsplit(opt$vars_to_regress, ",")) + +# Now we're hapy with the arguments, load Seurat and do the work + +suppressPackageStartupMessages(require(Seurat)) +if(opt$input_format == "loom" | opt$output_format == "loom") { + suppressPackageStartupMessages(require(SeuratDisk)) +} else if(opt$input_format == "singlecellexperiment" | opt$output_format == "singlecellexperiment") { + suppressPackageStartupMessages(require(scater)) +} + +# Input from serialized R object + +seurat_object <- read_seurat4_object(input_path = opt$input_object_file, format = opt$input_format) +# https://stackoverflow.com/questions/9129673/passing-list-of-named-parameters-to-function +# might be useful +scaled_seurat_object <- ScaleData(seurat_object, + features = genes_use, + vars.to.regress = opt$vars_to_regress, + model.use = opt$model_use, + use.umi = opt$use_umi, + do.scale = !opt$do_not_scale, + do.center = !opt$do_not_center, + scale.max = opt$scale_max, + block.size = opt$block_size, + min.cells.to.block = opt$min_cells_to_block, + verbose = FALSE) + + +# Output to a serialized R object +write_seurat4_object(seurat_object = scaled_seurat_object, + output_path = opt$output_object_file, + format = opt$output_format)