annotate center_scale.R @ 1:a96cc346819c draft

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_center_scale commit 7865eb7eb9d862e9967fe519d28df705d973fbaf
author artbio
date Fri, 12 Jul 2019 11:44:50 -0400
parents bcbd7179d8ec
children 163befe5f05b
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1 options( show.error.messages=F,
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2 error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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3 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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4 warnings()
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5 library(optparse)
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6
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7 # Arguments
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8 option_list = list(
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9 make_option(
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10 '--data',
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11 default = NA,
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12 type = 'character',
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13 help = "Input file that contains values to transform. Must be tabular separated,
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14 with columns and row names, variables in rows, observations in columns [default : '%default' ]"
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15 ),
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16 make_option(
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17 '--center',
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18 default = TRUE,
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19 type = 'logical',
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20 help = "center data to the mean [default : '%default' ]"
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21 ),
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22 make_option(
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23 '--scale',
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24 default = TRUE,
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25 type = 'logical',
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26 help = "scale data to standard deviation [default : '%default' ]"
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27 ),
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28 make_option(
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29 '--factor',
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30 default = '',
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31 type = 'character',
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32 help = "A two-column observations|factor_levels table, to group observations to be transformed by levels [default : '%default' ]"
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33 ),
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34 make_option(
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35 '--output',
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36 default = 'res.tab',
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37 type = 'character',
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38 help = "Table of transformed values [default : '%default' ]"
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39 )
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40 )
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41
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42 transform <- function(df, center=TRUE, scale=TRUE) {
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43 transfo <- scale(
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44 t(df),
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45 center=center,
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46 scale=scale
0
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47 )
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48 return(as.data.frame(t(transfo)))
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49 }
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50
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51 opt = parse_args(OptionParser(option_list = option_list),
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52 args = commandArgs(trailingOnly = TRUE))
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53
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54 data = read.table(
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55 opt$data,
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56 check.names = FALSE,
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57 header = TRUE,
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58 row.names = 1,
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59 sep = '\t'
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60 )
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61
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62 if (opt$factor != '') {
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63 data.factor = read.table(
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64 opt$factor,
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65 check.names = FALSE,
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66 header = TRUE,
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67 sep = '\t'
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68 )
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69 colnames(data.factor) <- c("cellid", "level")
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70 data.transformed <- data.frame(row.names=rownames(data), stringsAsFactors=FALSE)
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71 for (group in levels(data.factor$level)){
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72 subcells <- as.data.frame(subset(data.factor, level==group, select=cellid))
1
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73 subdata <- as.data.frame(subset(data, select=as.vector(subcells$cellid)))
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74 subdata.transformed <- transform(subdata, center=as.logical(opt$center),
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75 scale=as.logical(opt$scale))
0
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76 data.transformed <- cbind(data.transformed, subdata.transformed)
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77 }
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78 } else {
1
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79 data.transformed <- transform(data, center=as.logical(opt$center),
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80 scale=as.logical(opt$scale))
0
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81 }
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82
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83
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84 write.table(
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85 cbind(gene=rownames(data.transformed), data.transformed),
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86 opt$output,
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87 col.names = TRUE,
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88 row.names = FALSE,
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89 quote = F,
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90 sep = "\t"
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91 )
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