diff scater-plot-pca.R @ 0:4887c4c69847 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scater commit 5fdcafccb6c645d301db040dfeed693d7b6b4278
author iuc
date Thu, 18 Jul 2019 11:12:33 -0400
parents
children 81e5bdff4853
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/scater-plot-pca.R	Thu Jul 18 11:12:33 2019 -0400
@@ -0,0 +1,68 @@
+#!/usr/bin/env Rscript
+
+# Creates a PCA plot of a normalised SingleCellExperiment object.
+
+# Load optparse we need to check inputs
+
+library(optparse)
+library(workflowscriptscommon)
+library(LoomExperiment)
+library(scater)
+
+# parse options
+
+option_list = list(
+  make_option(
+    c("-i", "--input-loom"),
+    action = "store",
+    default = NA,
+    type = 'character',
+    help = "A SingleCellExperiment object file in Loom format."
+  ),
+  make_option(
+    c("-c", "--colour-by"),
+    action = "store",
+    default = NULL,
+    type = 'character',
+    help = "Feature (from annotation file) to colour PCA plot points by. The values represented in this options should be categorical"
+  ),
+  make_option(
+    c("-s", "--size-by"),
+    action = "store",
+    default = NULL,
+    type = 'character',
+    help = "Feature (from annotation file) to size PCA plot points by. The values represented in this options should be numerical and not categorical"
+  ),
+  make_option(
+    c("-p", "--shape-by"),
+    action = "store",
+    default = NULL,
+    type = 'character',
+    help = "Feature (from annotation file) to shape PCA plot points by. The values represented in this options should be categorical"
+  ),
+  make_option(
+    c("-o", "--output-plot-file"),
+    action = "store",
+    default = NA,
+    type = 'character',
+    help = "Path of the PDF output file to save plot to."
+  )
+)
+
+opt <- wsc_parse_args(option_list, mandatory = c('input_loom', 'output_plot_file'))
+# Check parameter values
+
+if ( ! file.exists(opt$input_loom)){
+  stop((paste('File', opt$input_loom, 'does not exist')))
+}
+
+
+# Input from Loom format
+
+scle <- import(opt$input_loom, format='loom', type='SingleCellLoomExperiment')
+scle <- normalize(scle, exprs_values = 1)
+scle <- runPCA(scle)
+plot <- plotReducedDim(scle, "PCA", colour_by = opt$colour_by, size_by = opt$size_by, shape_by = opt$shape_by)
+#do the scatter plot of reads vs genes
+
+ggsave(opt$output_plot_file, plot, device="pdf")