annotate scater-plot-tsne.R @ 3:ef4c80837bc5 draft default tip

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scater commit 9961b5acbf9081f10e14bc272406b36854fa2924"
author iuc
date Mon, 08 Nov 2021 12:02:13 +0000
parents 81e5bdff4853
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1 #!/usr/bin/env Rscript
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3 # Creates a t-SNE plot of a normalised SingleCellExperiment object.
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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 library(Rtsne)
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12
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13 # parse options
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15 option_list <- list(
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16 make_option(
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17 c("-i", "--input-loom"),
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18 action = "store",
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19 default = NA,
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20 type = "character",
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21 help = "A SingleCellExperiment object file in Loom format."
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22 ),
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23 make_option(
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24 c("-c", "--colour-by"),
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25 action = "store",
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26 default = NULL,
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27 type = "character",
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28 help = "Feature (from annotation file) to colour t-SNE plot points by. The values represented in this options should be categorical"
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29 ),
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30 make_option(
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31 c("-s", "--size-by"),
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32 action = "store",
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33 default = NULL,
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34 type = "character",
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35 help = "Feature (from annotation file) to size t-SNE plot points by. The values represented in this options should be numerical and not categorical"
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36 ),
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37 make_option(
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38 c("-p", "--shape-by"),
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39 action = "store",
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40 default = NULL,
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41 type = "character",
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42 help = "Feature (from annotation file) to shape t-SNE plot points by. The values represented in this options should be categorical"
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43 ),
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44 make_option(
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45 c("-o", "--output-plot-file"),
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46 action = "store",
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47 default = NA,
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48 type = "character",
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49 help = "Path of the PDF output file to save plot to."
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50 )
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51 )
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52
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53 opt <- wsc_parse_args(option_list, mandatory = c("input_loom", "output_plot_file"))
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54
1
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55 # Check parameter values
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56
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57 if (! file.exists(opt$input_loom)) {
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58 stop((paste("File", opt$input_loom, "does not exist")))
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59 }
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61 # Filter out unexpressed features
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63 sce <- import(opt$input_loom, format = "loom", type = "SingleCellLoomExperiment")
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64 sce <- logNormCounts(sce)
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65 sce <- runTSNE(sce, perplexity = 10)
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66 plot <- plotTSNE(sce, colour_by = opt$colour_by, size_by = opt$size_by, shape_by = opt$shape_by)
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68 ggsave(opt$output_plot_file, plot, device = "pdf")