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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit 9ab82433f375b37be5c9acb22e5deb798081dc3b
author artbio
date Thu, 07 Nov 2024 22:02:01 +0000
parents 6864acb21714
children
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cc768b0f41cf planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit 9ab82433f375b37be5c9acb22e5deb798081dc3b
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1 options(
cc768b0f41cf planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit 9ab82433f375b37be5c9acb22e5deb798081dc3b
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2 show.error.messages = FALSE,
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3 error = function() {
cc768b0f41cf planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit 9ab82433f375b37be5c9acb22e5deb798081dc3b
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4 cat(geterrmessage(), file = stderr())
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5 q("no", 1, FALSE)
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6 }
1
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7 )
0
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8 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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9 warnings()
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10
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11 library(optparse)
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12 library(scran)
2
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13 library(dynamicTreeCut)
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14
1
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15 # Arguments
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16 option_list <- list(
3
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17 make_option(
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18 c("-d", "--data"),
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19 default = NA,
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20 type = "character",
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21 help = "Input file that contains count values to transform"
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22 ),
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23 make_option(
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24 "--cluster",
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25 default = FALSE,
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26 action = "store_true",
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27 type = "logical",
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28 help = "Whether to calculate the size factor per cluster or on all cell"
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29 ),
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30 make_option(
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31 c("-m", "--method"),
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32 default = "hclust",
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33 type = "character",
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34 help = "The clustering method to use for grouping cells into cluster : hclust or igraph [default : '%default' ]"
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35 ),
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36 make_option(
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37 "--size",
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38 default = 100,
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39 type = "integer",
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40 help = "Minimal number of cells in each cluster : hclust or igraph [default : '%default' ]"
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41 ),
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42 make_option(
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43 c("-o", "--out"),
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44 default = "res.tab",
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45 type = "character",
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46 help = "Output name [default : '%default' ]"
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47 )
0
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48 )
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49
1
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50 opt <- parse_args(OptionParser(option_list = option_list),
3
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51 args = commandArgs(trailingOnly = TRUE)
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52 )
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1
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55 data <- read.table(
3
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56 opt$data,
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57 check.names = FALSE,
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58 header = TRUE,
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59 row.names = 1,
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60 sep = "\t"
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61 )
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63 ## Import data as a SingleCellExperiment object
1
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64 sce <- SingleCellExperiment(list(counts = as.matrix(data)))
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66 if (opt$cluster) {
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67 clusters <- quickCluster(sce, min.size = opt$size, method = opt$method)
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68
3
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69 ## Compute sum factors
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70 sce <- computeSumFactors(sce, cluster = clusters)
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71 } else {
3
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72 ## Compute sum factors
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73 sce <- computeSumFactors(sce)
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74 }
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75
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76 sce <- logNormCounts(sce)
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78 logcounts <- data.frame(genes = rownames(sce), round(logcounts(sce), digits = 5), check.names = FALSE)
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81 write.table(
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82 logcounts,
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83 opt$out,
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84 col.names = TRUE,
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85 row.names = FALSE,
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86 quote = FALSE,
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87 sep = "\t"
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252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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88 )