annotate mqppep_anova.R @ 2:a5e7469dfdfa draft

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 423304b26e63d23cd8e5fb4c2fb729c5beea1254
author galaxyp
date Mon, 12 Dec 2022 22:01:21 +0000
parents b76c75521d91
children bae3a23461c9
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1 #!/usr/bin/env Rscript
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2 # libraries
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3 library(optparse)
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4 library(stringr)
1
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5 library(tinytex)
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6
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7 # ref for parameterizing Rmd document: https://stackoverflow.com/a/37940285
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8
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9 # parse options
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10 option_list <- list(
1
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11
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12 # files
0
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13 make_option(
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14 c("-a", "--alphaFile"),
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15 action = "store",
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16 default = NA,
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17 type = "character",
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18 help = paste0("List of alpha cutoff values for significance testing;",
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19 " path to text file having one column and no header")
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20 ),
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21 make_option(
1
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22 c("-M", "--anova_ksea_metadata"),
0
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23 action = "store",
1
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24 default = "anova_ksea_metadata.tsv",
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25 type = "character",
1
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26 help = "Phosphopeptide metadata, ANOVA FDR, and KSEA enribhments"
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27 ),
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28 make_option(
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29 c("-o", "--imputedDataFile"),
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30 action = "store",
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31 default = "output_imputed.tsv",
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32 type = "character",
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33 help = "Imputed Phosphopeptide Intensities output file path"
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34 ),
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35 make_option(
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36 c("-n", "--imputedQNLTDataFile"),
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37 action = "store",
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38 default = "output_imp_qn_lt.tsv",
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39 type = "character",
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40 help =
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41 paste(
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42 "Imputed, Quantile-Normalized Log-Transformed Phosphopeptide",
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43 "Intensities output file path"
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44 )
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45 ),
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46 make_option(
1
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47 c("-i", "--inputFile"),
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48 action = "store",
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49 default = NA,
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50 type = "character",
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51 help = "Phosphopeptide Intensities sparse input file path"
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52 ),
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53 make_option(
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54 c("-K", "--ksea_sqlite"),
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55 action = "store",
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56 default = NA,
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57 type = "character",
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58 help = "Path to 'ksea_sqlite' output produced by this tool"
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59 ),
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60 make_option(
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61 c("-S", "--preproc_sqlite"),
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62 action = "store",
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63 default = NA,
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64 type = "character",
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65 help = "Path to 'preproc_sqlite' produced by `mqppep_mrgfltr.py`"
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66 ),
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67 make_option(
0
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68 c("-r", "--reportFile"),
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69 action = "store",
1
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70 default = "mqppep_anova.pdf",
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71 type = "character",
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72 help = "PDF report file path"
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73 ),
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74
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75 # parameters
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76 make_option(
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77 c("-f", "--firstDataColumn"),
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78 action = "store",
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79 default = "^Intensity[^_]",
0
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80 type = "character",
1
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81 help = "First column of intensity values"
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82 ),
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83 make_option(
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84 c("-m", "--imputationMethod"),
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85 action = "store",
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86 default = "random",
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87 type = "character",
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88 help = paste0("Method for missing-value imputation,",
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89 " one of c('group-median','median','mean','random')")
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90 ),
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91 make_option(
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92 c("-C", "--intensityMinValuesPerClass"),
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93 action = "store",
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94 default = "0",
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95 type = "integer",
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96 help = "Minimum number of observed values per class"
0
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diff changeset
97 ),
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98 make_option(
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99 c("-k", "--ksea_cutoff_statistic"),
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100 action = "store",
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101 default = "FDR",
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102 type = "character",
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103 help = paste0("Method for missing-value imputation,",
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104 " one of c('FDR','p.value'), but don't expect 'p.value' to work well.")
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105 ),
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106 make_option(
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107 c("-t", "--ksea_cutoff_threshold"),
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108 action = "store",
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109 default = 0.05,
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110 type = "double",
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111 help = paste0("Maximum score to be used to score a kinase enrichment as significant")
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112 ),
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113 make_option(
1
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114 c("-c", "--kseaMinSubstrateCount"),
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115 action = "store",
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116 default = "1",
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117 type = "integer",
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118 help = "Minimum number of substrates to consider any kinase for KSEA"
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119 ),
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120 make_option(
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121 c("--kseaUseAbsoluteLog2FC"),
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122 action = "store_true",
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123 default = "FALSE",
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124 type = "logical",
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125 help = paste0("Should abs(log2(fold-change)) be used for KSEA?",
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126 " (TRUE may alter number of hits.)")
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127 ),
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128 make_option(
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129 c("-p", "--meanPercentile"),
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130 action = "store",
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131 default = 3,
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132 type = "integer",
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133 help = paste0("Mean percentile for randomly generated imputed values;",
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134 ", range [1,99]")
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135 ),
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136 make_option(
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137 c("--minQuality"),
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138 action = "store",
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139 default = 0,
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140 type = "integer",
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141 help = paste0("Minimum quality (higher value reduces number of substrates",
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142 " accepted; you may want to keep below 100), range [0,infinity]")
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143 ),
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144 make_option(
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145 c("--oneWayManyCategories"),
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146 action = "store",
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147 default = "aov",
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148 type = "character",
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149 help = "Name of R function for one-way tests among more than two categories"
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150 ),
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151 make_option(
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152 c("--oneWayTwoCategories"),
0
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153 action = "store",
1
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154 default = "two.way",
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155 type = "character",
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156 help = "Name of R function for one-way tests between two categories"
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157 ),
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158 make_option(
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159 c("-s", "--regexSampleNames"),
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160 action = "store",
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161 default = "\\.(\\d+)[A-Z]$",
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162 type = "character",
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163 help = "Regular expression extracting sample-names"
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164 ),
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165 make_option(
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166 c("-g", "--regexSampleGrouping"),
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167 action = "store",
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168 default = "(\\d+)",
0
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169 type = "character",
1
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170 help = paste0("Regular expression extracting sample-group",
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171 " from an extracted sample-name")
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172 ),
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173 make_option(
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174 c("-d", "--sdPercentile"),
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175 action = "store",
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176 default = 3,
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177 type = "double",
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178 help = paste0("Adjustment value for standard deviation of",
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179 " randomly generated imputed values; real")
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180 ),
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181 make_option(
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182 c("-F", "--sampleGroupFilter"),
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183 action = "store",
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184 default = "none",
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185 type = "character",
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186 help = paste0("Should no filter be applied to sample group names (none)",
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187 " or should the filter specify samples to include or exclude?")
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188 ),
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189 make_option(
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190 c("--sampleGroupFilterMode"),
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191 action = "store",
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192 default = "r",
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193 type = "character",
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194 help = paste0("First character ('f', 'p', or 'r') indicating regular",
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195 "expression matching mode ('fixed', 'perl', or 'grep'; ",
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196 "see https://rdrr.io/r/base/grep.html). Second character may be 'i;",
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197 "to make search ignore case.")
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198 ),
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199 make_option(
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200 c("-G", "--sampleGroupFilterPatterns"),
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201 action = "store",
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202 default = ".*",
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203 type = "character",
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204 help = paste0("Regular expression extracting sample-group",
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205 " from an extracted sample-name")
0
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206 )
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207 )
1
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208
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209 tryCatch(
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210 args <- parse_args(
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211 OptionParser(
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212 option_list = option_list,
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213 add_help_option = TRUE
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214 ),
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215 print_help_and_exit = TRUE
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216 ),
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217 error = function(e) {
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218 parse_args(
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219 OptionParser(
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220 option_list = option_list,
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221 add_help_option = TRUE
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222 ),
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223 print_help_and_exit = TRUE
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224 )
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225 stop(as.character(e))
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226 }
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227 )
0
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228 print("args is:")
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229 cat(str(args))
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230
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231 # Check parameter values
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232
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233 if (! file.exists(args$inputFile)) {
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234 stop((paste("Input file", args$inputFile, "does not exist")))
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235 }
1
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236
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237 # files
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238 alpha_file <- args$alphaFile
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239 anova_ksea_metadata_file <- args$anova_ksea_metadata
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240 imp_qn_lt_data_file <- args$imputedQNLTDataFile
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241 imputed_data_file <- args$imputedDataFile
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242 input_file <- args$inputFile
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243 ksea_sqlite_file <- args$ksea_sqlite
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244 preproc_sqlite_file <- args$preproc_sqlite
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245 report_file_name <- args$reportFile
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246
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247 # parameters
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248 # firstDataColumn - see below
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249 group_filter <- args$sampleGroupFilter
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250 group_filter_mode <- args$sampleGroupFilterMode
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251 # imputationMethod - see below
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252 intensity_min_values_per_class <- args$intensityMinValuesPerClass
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253 ksea_cutoff_statistic <- args$ksea_cutoff_statistic
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254 ksea_cutoff_threshold <- args$ksea_cutoff_threshold
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255 ksea_min_substrate_count <- args$kseaMinSubstrateCount
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256 ksea_use_absolute_log2_fc <- args$kseaUseAbsoluteLog2FC
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257 # mean_percentile - see below
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258 min_quality <- args$minQuality
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259 # regexSampleNames - see below
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260 # regexSampleGrouping - see below
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261 # sampleGroupFilterPatterns - see below (becomes group_filter_patterns)
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262 # sd_percentile - see below
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263
0
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264 if (
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265 sum(
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266 grepl(
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267 pattern = ksea_cutoff_statistic,
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268 x = c("FDR", "p.value")
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269 )
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270 ) < 1
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271 ) {
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272 print(sprintf("bad ksea_cutoff_statistic argument: %s", ksea_cutoff_statistic))
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273 return(-1)
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274 }
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275
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276 imputation_method <- args$imputationMethod
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277 if (
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278 sum(
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279 grepl(
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280 pattern = imputation_method,
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281 x = c("group-median", "median", "mean", "random")
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282 )
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283 ) < 1
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284 ) {
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285 print(sprintf("bad imputationMethod argument: %s", imputation_method))
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286 return(-1)
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287 }
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288
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289 # read with default values, when applicable
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290 mean_percentile <- args$meanPercentile
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291 sd_percentile <- args$sdPercentile
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292 # in the case of 'random" these values are ignored by the client script
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293 if (imputation_method == "random") {
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294 print("mean_percentile is:")
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295 cat(str(mean_percentile))
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296
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297 print("sd_percentile is:")
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298 cat(str(mean_percentile))
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299 }
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300
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301 # convert string parameters that are passed in via config files:
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302 # - firstDataColumn
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303 # - regexSampleNames
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304 # - regexSampleGrouping
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305 read_config_file_string <- function(fname, limit) {
1
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306 cat(sprintf("read_config_file_string: fname = '%s'\n", fname))
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307 cat(sprintf("length(fname) = '%s'\n", length(fname)))
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308 result <-
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309 if (file.exists(fname)) {
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310 cat(sprintf("reading '%s' ...\n", fname))
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311 readChar(fname, limit)
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312 } else {
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313 cat(sprintf("not a file: '%s'\n", fname))
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314 fname
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315 }
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316 #AC print(paste0("read_config_file_string: opening file '", as.character(fname), "'"))
0
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317 # eliminate any leading whitespace
1
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318 result <- gsub("^[ \t\n]*", "", result)
0
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319 # eliminate any trailing whitespace
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320 result <- gsub("[ \t\n]*$", "", result)
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321 # substitute characters escaped by Galaxy sanitizer
1
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322 result <- gsub("__lt__", "<", result)
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323 result <- gsub("__le__", "<=", result)
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324 result <- gsub("__eq__", "==", result)
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325 result <- gsub("__ne__", "!=", result)
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326 result <- gsub("__gt__", ">", result)
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327 result <- gsub("__ge__", ">=", result)
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328 result <- gsub("__sq__", "'", result)
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329 result <- gsub("__dq__", '"', result)
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330 result <- gsub("__ob__", "[", result)
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331 result <- gsub("__cb__", "]", result)
0
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332 }
1
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333 nc <- 1000
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334
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335 sink(stderr())
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336
0
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337 cat(paste0("first_data_column file: ", args$firstDataColumn, "\n"))
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338 first_data_column <- read_config_file_string(args$firstDataColumn, nc)
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339 cat(paste0("first_data_column: ", first_data_column, "\n"))
1
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340
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341 cat(paste0("regex_sample_grouping file: ", args$regexSampleGrouping, "\n"))
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342 regex_sample_grouping <- read_config_file_string(args$regexSampleGrouping, nc)
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343 cat(paste0("regex_sample_grouping: ", regex_sample_grouping, "\n"))
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344
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345 cat(paste0("regex_sample_names file: ", args$regexSampleNames, "\n"))
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346 regex_sample_names <- read_config_file_string(args$regexSampleNames, nc)
0
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347 cat(paste0("regex_sample_names: ", regex_sample_names, "\n"))
1
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348
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349 if (group_filter != "none") {
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350 cat(paste0("group_filter_patterns file: '", args$sampleGroupFilterPatterns, "'\n"))
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351 group_filter_patterns <- read_config_file_string(args$sampleGroupFilterPatterns, nc)
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352 } else {
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353 group_filter_patterns <- ".*"
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354 }
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355 cat(paste0("group_filter_patterns: ", group_filter_patterns, "\n"))
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356
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357 sink()
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358
0
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359
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360 # from: https://github.com/molgenis/molgenis-pipelines/wiki/
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361 # How-to-source-another_file.R-from-within-your-R-script
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362 # Function location_of_this_script returns the location of this .R script
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363 # (may be needed to source other files in same dir)
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364 location_of_this_script <- function() {
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365 this_file <- NULL
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366 # This file may be 'sourced'
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367 for (i in - (1:sys.nframe())) {
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368 if (identical(sys.function(i), base::source)) {
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369 this_file <- (normalizePath(sys.frame(i)$ofile))
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370 }
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371 }
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372
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373 if (!is.null(this_file)) return(dirname(this_file))
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374
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375 # But it may also be called from the command line
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376 cmd_args <- commandArgs(trailingOnly = FALSE)
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377 cmd_args_trailing <- commandArgs(trailingOnly = TRUE)
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378 cmd_args <- cmd_args[
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379 seq.int(
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380 from = 1,
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381 length.out = length(cmd_args) - length(cmd_args_trailing)
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382 )
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383 ]
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384 res <- gsub("^(?:--file=(.*)|.*)$", "\\1", cmd_args)
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385
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386 # If multiple --file arguments are given, R uses the last one
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387 res <- tail(res[res != ""], 1)
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388 if (0 < length(res)) return(dirname(res))
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389
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390 # Both are not the case. Maybe we are in an R GUI?
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391 return(NULL)
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392 }
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393
1
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394 # validation of input parameters is complete; it is now justifiable to
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395 # install LaTeX tools to render markdown as PDF; this involves a big
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diff changeset
396 # download from GitHub
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397 if (!tinytex::is_tinytex()) tinytex::install_tinytex()
0
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398
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399 rmarkdown_params <- list(
1
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400
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diff changeset
401 # files
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diff changeset
402 alphaFile = alpha_file
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403 , anovaKseaMetadata = anova_ksea_metadata_file
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404 , imputedDataFilename = imputed_data_file
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405 , imputedQNLTDataFile = imp_qn_lt_data_file
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406 , inputFile = input_file
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407 , kseaAppPrepDb = ksea_sqlite_file
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408 , preprocDb = preproc_sqlite_file
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diff changeset
409
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diff changeset
410 # parameters
0
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411 , firstDataColumn = first_data_column
1
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412 , groupFilter = group_filter
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413 , groupFilterMode = group_filter_mode # arg sampleGroupFilterMode
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414 , groupFilterPatterns = group_filter_patterns # arg sampleGroupFilterPatterns
0
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415 , imputationMethod = imputation_method
1
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416 , intensityMinValuesPerGroup = intensity_min_values_per_class
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417 , kseaCutoffStatistic = ksea_cutoff_statistic
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418 , kseaCutoffThreshold = ksea_cutoff_threshold
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419 , kseaMinSubstrateCount = ksea_min_substrate_count
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420 , kseaUseAbsoluteLog2FC = ksea_use_absolute_log2_fc # add
0
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421 , meanPercentile = mean_percentile
1
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422 , minQuality = min_quality # add
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423 , regexSampleGrouping = regex_sample_grouping
0
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424 , regexSampleNames = regex_sample_names
1
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425 , sdPercentile = sd_percentile
0
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426 )
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427
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428 print("rmarkdown_params")
1
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429 print(rmarkdown_params)
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430 print(
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431 lapply(
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432 X = rmarkdown_params,
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433 FUN = function(x) {
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434 paste0(
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435 nchar(as.character(x)),
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436 ": '",
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437 as.character(x),
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438 "'"
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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439 )
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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440 }
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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441 )
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
galaxyp
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442 )
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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443
0
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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444
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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445 # freeze the random number generator so the same results will be produced
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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446 # from run to run
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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447 set.seed(28571)
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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448
1
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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449 script_dir <- location_of_this_script()
0
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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450
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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451 rmarkdown::render(
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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452 input = paste(script_dir, "mqppep_anova_script.Rmd", sep = "/")
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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453 , output_file = report_file_name
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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454 , params = rmarkdown_params
1
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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455 , output_format = rmarkdown::pdf_document(
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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456 includes = rmarkdown::includes(in_header = "mqppep_anova_preamble.tex")
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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457 , dev = "pdf"
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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458 , toc = TRUE
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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459 , toc_depth = 2
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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460 , number_sections = FALSE
b76c75521d91 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 43e7a43b545c24b2dc33d039198551c032aa79be
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461 )
0
8dfd5d2b5903 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 3a7b3609d6e514c9e8f980ecb684960c6b2252fe
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462 )