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annotate scater-plot-pca.R @ 3:652923ce664f draft default tip

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scater commit 9961b5acbf9081f10e14bc272406b36854fa2924"
author iuc
date Mon, 08 Nov 2021 12:03:34 +0000
parents 7a365ec81b52
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1 #!/usr/bin/env Rscript
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3 # Creates a PCA plot of a normalised SingleCellExperiment object.
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4
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5 # Load optparse we need to check inputs
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6
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7 library(optparse)
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8 library(workflowscriptscommon)
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9 library(LoomExperiment)
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10 library(scater)
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11
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12 # parse options
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13
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7a365ec81b52 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scater commit 154318f74839a4481c7c68993c4fb745842c4cce"
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14 option_list <- list(
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15 make_option(
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16 c("-i", "--input-loom"),
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17 action = "store",
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18 default = NA,
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19 type = "character",
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20 help = "A SingleCellExperiment object file in Loom format."
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21 ),
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22 make_option(
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23 c("-c", "--colour-by"),
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24 action = "store",
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25 default = NULL,
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26 type = "character",
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27 help = "Feature (from annotation file) to colour PCA plot points by. The values represented in this options should be categorical"
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28 ),
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29 make_option(
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30 c("-s", "--size-by"),
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31 action = "store",
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32 default = NULL,
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33 type = "character",
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34 help = "Feature (from annotation file) to size PCA plot points by. The values represented in this options should be numerical and not categorical"
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35 ),
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36 make_option(
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37 c("-p", "--shape-by"),
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38 action = "store",
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39 default = NULL,
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40 type = "character",
0
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41 help = "Feature (from annotation file) to shape PCA plot points by. The values represented in this options should be categorical"
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42 ),
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43 make_option(
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44 c("-o", "--output-plot-file"),
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45 action = "store",
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46 default = NA,
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47 type = "character",
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48 help = "Path of the PDF output file to save plot to."
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49 )
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50 )
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51
2
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52 opt <- wsc_parse_args(option_list, mandatory = c("input_loom", "output_plot_file"))
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53
0
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54 # Check parameter values
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55
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56 if (! file.exists(opt$input_loom)) {
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57 stop((paste("File", opt$input_loom, "does not exist")))
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58 }
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59
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60 # Filter out unexpressed features
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61
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62 sce <- import(opt$input_loom, format = "loom", type = "SingleCellLoomExperiment")
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63 sce <- logNormCounts(sce)
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64 sce <- runPCA(sce)
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65
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66 plot <- plotReducedDim(sce, dimred = "PCA", colour_by = opt$colour_by, size_by = opt$size_by, shape_by = opt$shape_by)
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67
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68 ggsave(opt$output_plot_file, plot, device = "pdf")