--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/scripts/seurat-scale-data.R	Sat Mar 02 10:42:01 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)