Mercurial > repos > eschen42 > w4mclassfilter

annotate w4mclassfilter_wrapper.R @ 13:c18040b6e8b9 draft

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"planemo upload for repository https://github.com/HegemanLab/w4mclassfilter_galaxy_wrapper/tree/master commit 1a5dd14c3697516bc55950bd6e46c978af7c19cf"
author eschen42
date Thu, 24 Oct 2019 10:21:23 -0400
parents 38f509903a0b
children 87ec0d3c2266
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1 #!/usr/bin/env Rscript
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2
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3 library(batch) ## parseCommandArgs
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4
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5 ########
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6 # MAIN #
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7 ########
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8
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9 argVc <- unlist(parseCommandArgs(evaluate=FALSE))
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11 ##------------------------------
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12 ## Initializing
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13 ##------------------------------
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14
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15 ## options
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16 ##--------
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17
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18 strAsFacL <- options()$stringsAsFactors
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19 options(stringsAsFactors = FALSE)
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20
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21 ## libraries
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22 ##----------
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23
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24 suppressMessages(library(w4mclassfilter))
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25
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26 if(packageVersion("w4mclassfilter") < "0.98.12")
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27 stop("Please use 'w4mclassfilter' versions of 0.98.12 and above")
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28
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29 ## constants
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30 ##----------
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31
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32 modNamC <- "w4mclassfilter" ## module name
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33
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34 topEnvC <- environment()
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35 flgC <- "\n"
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36
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37 ## functions
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38 ##----------
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39
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40 flgF <- function(tesC,
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41 envC = topEnvC,
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42 txtC = NA) { ## management of warning and error messages
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43
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44 tesL <- eval(parse(text = tesC), envir = envC)
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45
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46 if(!tesL) {
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47
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48 #sink(NULL)
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49 stpTxtC <- ifelse(is.na(txtC),
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50 paste0(tesC, " is FALSE"),
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51 txtC)
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52
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53 stop(stpTxtC,
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54 call. = FALSE)
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55
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56 }
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57
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58 } ## flgF
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59
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60
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61 ## log file
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62 ##---------
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63
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64 my_print <- function(x, ...) { cat(c(x, ...))}
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65
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66 my_print("\nStart of the '", modNamC, "' Galaxy module call: ",
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67 format(Sys.time(), "%a %d %b %Y %X"), "\n", sep="")
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68
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69 ## arguments
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70 ##----------
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71
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72 # files
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73
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74 dataMatrix_in <- as.character(argVc["dataMatrix_in"])
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75 dataMatrix_out <- as.character(argVc["dataMatrix_out"])
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76
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77 sampleMetadata_in <- as.character(argVc["sampleMetadata_in"])
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78 sampleMetadata_out <- as.character(argVc["sampleMetadata_out"])
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79
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80 variableMetadata_in <- as.character(argVc["variableMetadata_in"])
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81 variableMetadata_out <- as.character(argVc["variableMetadata_out"])
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82
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83 # other parameters
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84
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85 transformation <- as.character(argVc["transformation"])
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86 my_imputation_label <- as.character(argVc["imputation"])
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87 my_imputation_function <- if (my_imputation_label == "zero") {
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88 w4m_filter_zero_imputation
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89 } else if (my_imputation_label == "center") {
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90 w4m_filter_median_imputation
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91 } else if (my_imputation_label == "none") {
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92 w4m_filter_no_imputation
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93 } else {
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94 stop(sprintf("Unknown value %s supplied for 'imputation' parameter. Expected one of {zero,center,none}."))
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95 }
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96 wildcards <- as.logical(argVc["wildcards"])
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97 sampleclassNames <- as.character(argVc["sampleclassNames"])
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98 sampleclassNames <- strsplit(x = sampleclassNames, split = ",", fixed = TRUE)[[1]]
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99 if (wildcards) {
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100 sampleclassNames <- gsub("[.]", "[.]", sampleclassNames)
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101 sampleclassNames <- utils::glob2rx(sampleclassNames, trim.tail = FALSE)
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102 }
0
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103 inclusive <- as.logical(argVc["inclusive"])
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104 classnameColumn <- as.character(argVc["classnameColumn"])
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105 samplenameColumn <- as.character(argVc["samplenameColumn"])
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106
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107 order_smpl <- as.character(argVc["order_smpl"])
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108 order_vrbl <- as.character(argVc["order_vrbl"])
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109
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110 variable_range_filter <- as.character(argVc["variable_range_filter"])
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111 variable_range_filter <- strsplit(x = variable_range_filter, split = ",", fixed = TRUE)[[1]]
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112
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113 ## -----------------------------
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114 ## Transformation and imputation
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115 ## -----------------------------
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116 my_transformation_and_imputation <- if (transformation == "log10") {
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117 function(m) {
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118 if (!is.matrix(m))
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119 stop("Cannot transform and impute data - the supplied data is not in matrix form")
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120 if (nrow(m) == 0)
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121 stop("Cannot transform and impute data - data matrix has no rows")
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122 if (ncol(m) == 0)
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123 stop("Cannot transform and impute data - data matrix has no columns")
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124 suppressWarnings({
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125 # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
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126 m <- log10(m)
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127 m[is.na(m)] <- NA
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128 })
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129 return ( my_imputation_function(m) )
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130 }
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131 } else if (transformation == "log2") {
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132 function(m) {
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133 if (!is.matrix(m))
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134 stop("Cannot transform and impute data - the supplied data is not in matrix form")
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135 if (nrow(m) == 0)
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136 stop("Cannot transform and impute data - data matrix has no rows")
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137 if (ncol(m) == 0)
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138 stop("Cannot transform and impute data - data matrix has no columns")
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139 suppressWarnings({
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140 # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
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141 m <- log2(m)
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142 m[is.na(m)] <- NA
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143 })
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144 return ( my_imputation_function(m) )
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145 }
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146 } else {
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147 # use the method from the w4mclassfilter class
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148 my_imputation_function
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149 }
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150
0
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151 ##------------------------------
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152 ## Computation
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153 ##------------------------------
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154
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155 result <- w4m_filter_by_sample_class(
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156 dataMatrix_in = dataMatrix_in
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157 , sampleMetadata_in = sampleMetadata_in
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158 , variableMetadata_in = variableMetadata_in
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159 , dataMatrix_out = dataMatrix_out
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160 , sampleMetadata_out = sampleMetadata_out
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161 , variableMetadata_out = variableMetadata_out
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162 , classes = sampleclassNames
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163 , include = inclusive
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164 , class_column = classnameColumn
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165 , samplename_column = samplenameColumn
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166 , order_vrbl = order_vrbl
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167 , order_smpl = order_smpl
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168 , variable_range_filter = variable_range_filter
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169 , failure_action = my_print
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170 , data_imputation = my_transformation_and_imputation
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171 )
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172
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173 my_print("\nResult of '", modNamC, "' Galaxy module call to 'w4mclassfilter::w4m_filter_by_sample_class' R function: ",
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174 as.character(result), "\n", sep = "")
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175
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176 ##--------
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177 ## Closing
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178 ##--------
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179
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180 my_print("\nEnd of '", modNamC, "' Galaxy module call: ",
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181 as.character(Sys.time()), "\n", sep = "")
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182
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183 #sink()
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184
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185 if (!file.exists(dataMatrix_out)) {
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186 print(sprintf("ERROR %s::w4m_filter_by_sample_class - file '%s' was not created", modNamC, dataMatrix_out))
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187 }# else { print(sprintf("INFO %s::w4m_filter_by_sample_class - file '%s' was exists", modNamC, dataMatrix_out)) }
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188
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189 if (!file.exists(variableMetadata_out)) {
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190 print(sprintf("ERROR %s::w4m_filter_by_sample_class - file '%s' was not created", modNamC, variableMetadata_out))
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191 } # else { print(sprintf("INFO %s::w4m_filter_by_sample_class - file '%s' was exists", modNamC, variableMetadata_out)) }
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192
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193 if (!file.exists(sampleMetadata_out)) {
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194 print(sprintf("ERROR %s::w4m_filter_by_sample_class - file '%s' was not created", modNamC, sampleMetadata_out))
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195 } # else { print(sprintf("INFO %s::w4m_filter_by_sample_class - file '%s' was exists", modNamC, sampleMetadata_out)) }
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196
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197 if( !result ) {
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198 stop(sprintf("ERROR %s::w4m_filter_by_sample_class - method failed", modNamC))
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199 }
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200
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201 rm(list = ls())