Mercurial > repos > iuc > scater_filter

comparison scater-pca-filter.R @ 2:7a365ec81b52 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scater commit 154318f74839a4481c7c68993c4fb745842c4cce"
author iuc
date Thu, 09 Sep 2021 12:24:17 +0000
parents e6ca62ac65c6
children
comparison
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1:b7ea9f09c02f 2:7a365ec81b52
10 # Load optparse we need to check inputs 10 # Load optparse we need to check inputs
11 library(optparse) 11 library(optparse)
12 library(workflowscriptscommon) 12 library(workflowscriptscommon)
13 library(LoomExperiment) 13 library(LoomExperiment)
14 library(scater) 14 library(scater)
15 library(mvoutlier) 15 library(robustbase)
16 16
17 # parse options 17 # parse options
18 option_list = list( 18 option_list <- list(
19 make_option( 19 make_option(
20 c("-i", "--input-loom"), 20 c("-i", "--input-loom"),
21 action = "store", 21 action = "store",
22 default = NA, 22 default = NA,
23 type = 'character', 23 type = "character",
24 help = "A SingleCellExperiment object file in Loom format." 24 help = "A SingleCellExperiment object file in Loom format."
25 ), 25 ),
26 make_option( 26 make_option(
27 c("-o", "--output-loom"), 27 c("-o", "--output-loom"),
28 action = "store", 28 action = "store",
29 default = NA, 29 default = NA,
30 type = 'character', 30 type = "character",
31 help = "File name in which to store the SingleCellExperiment object in Loom format." 31 help = "File name in which to store the SingleCellExperiment object in Loom format."
32 ) 32 )
33 ) 33 )
34 34
35 opt <- wsc_parse_args(option_list, mandatory = c('input_loom', 'output_loom')) 35 opt <- wsc_parse_args(option_list, mandatory = c("input_loom", "output_loom"))
36 36
37 # Check parameter values 37 # Check parameter values
38 38
39 if ( ! file.exists(opt$input_loom)){ 39 if (! file.exists(opt$input_loom)) {
40 stop((paste('File', opt$input_loom, 'does not exist'))) 40 stop((paste("File", opt$input_loom, "does not exist")))
41 } 41 }
42 42
43 # Input from Loom format 43 # Filter out unexpressed features
44 44
45 scle <- import(opt$input_loom, format='loom', type='SingleCellLoomExperiment') 45 sce <- import(opt$input_loom, format = "loom", type = "SingleCellLoomExperiment")
46 print(paste("Starting with", ncol(scle), "cells and", nrow(scle), "features."))
47 46
48 # Run PCA on data and detect outliers 47 print(paste("Starting with", ncol(sce), "cells"))
49 scle <- runPCA(scle, use_coldata = TRUE, detect_outliers = TRUE)
50 48
51 # Filter out outliers 49 sce <- runColDataPCA(sce, outliers = TRUE, variables = list("sum", "detected", "subsets_Mito_percent"))
52 scle <- scle[, !scle$outlier] 50 sce$use <- !sce$outlier
51 sce <- sce[, colData(sce)$use]
52 print(paste("Ending with", ncol(sce), "cells"))
53 53
54 print(paste("Ending with", ncol(scle), "cells and", nrow(scle), "features."))
55 54
56 # Output to a Loom file 55 # Output to a Loom file
57 if (file.exists(opt$output_loom)) { 56 if (file.exists(opt$output_loom)) {
58 file.remove(opt$output_loom) 57 file.remove(opt$output_loom)
59 } 58 }
60 export(scle, opt$output_loom, format='loom') 59 export(sce, opt$output_loom, format = "loom")