Mercurial > repos > recetox > waveica

annotate waveica_wrapper.R @ 2:6480c6d5fa36 draft

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/waveica commit 77bea6c84c5a932fa203723d4d5fea6147f06505
author recetox
date Fri, 23 Jun 2023 07:27:29 +0000
parents b77023c41c76
children dbbedb14b44c
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6480c6d5fa36 planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/waveica commit 77bea6c84c5a932fa203723d4d5fea6147f06505
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1 read_file <- function(file, metadata, ft_ext, mt_ext, transpose) {
1
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2 data <- read_data(file, ft_ext)
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3
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4 if (transpose) {
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5 col_names <- c("sampleName", data[[1]])
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6 t_data <- data[-1]
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7 t_data <- t(t_data)
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8 data <- data.frame(rownames(t_data), t_data)
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9 colnames(data) <- col_names
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10 }
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11
1
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12 if (!is.na(metadata)) {
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13 mt_data <- read_data(metadata, mt_ext)
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14 data <- merge(mt_data, data, by = "sampleName")
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15 }
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17 return(data)
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18 }
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20 read_data <- function(file, ext) {
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21 if (ext == "csv") {
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22 data <- read.csv(file, header = TRUE)
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23 } else if (ext == "tsv") {
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24 data <- read.csv(file, header = TRUE, sep = "\t")
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25 } else {
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26 data <- arrow::read_parquet(file)
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27 }
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29 return(data)
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30 }
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32 waveica <- function(file,
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33 metadata = NA,
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34 ext,
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35 transpose = FALSE,
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36 wavelet_filter,
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37 wavelet_length,
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38 k,
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39 t,
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40 t2,
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41 alpha,
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42 exclude_blanks) {
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43 # get input from the Galaxy, preprocess data
1
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44 ext <- strsplit(x = ext, split = "\\,")[[1]]
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46 ft_ext <- ext[1]
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47 mt_ext <- ext[2]
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48
2
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49 data <- read_file(file, metadata, ft_ext, mt_ext, transpose)
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2
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51 required_columns <- c(
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52 "sampleName", "class", "sampleType",
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53 "injectionOrder", "batch"
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54 )
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55 data <- verify_input_dataframe(data, required_columns)
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57 data <- sort_by_injection_order(data)
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58
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59 # separate data into features, batch and group
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60 feature_columns <- colnames(data)[!colnames(data) %in% required_columns]
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61 features <- data[, feature_columns]
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62 group <- enumerate_groups(as.character(data$sampleType))
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63 batch <- data$batch
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64
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65 # run WaveICA
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66 features <- recetox.waveica::waveica(
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67 data = features,
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68 wf = get_wf(wavelet_filter, wavelet_length),
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69 batch = batch,
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70 group = group,
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71 K = k,
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72 t = t,
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73 t2 = t2,
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74 alpha = alpha
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75 )
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76
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77 data[, feature_columns] <- features
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78
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79 # remove blanks from dataset
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80 if (exclude_blanks) {
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81 data <- exclude_group(data, group)
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82 }
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83
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84 return(data)
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85 }
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86
1
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87 waveica_singlebatch <- function(file,
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88 metadata = NA,
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89 ext,
2
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90 transpose = FALSE,
0
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91 wavelet_filter,
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92 wavelet_length,
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93 k,
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94 alpha,
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95 cutoff,
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96 exclude_blanks) {
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97 # get input from the Galaxy, preprocess data
1
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98 ext <- strsplit(x = ext, split = "\\,")[[1]]
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99
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100 ft_ext <- ext[1]
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101 mt_ext <- ext[2]
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102
2
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103 data <- read_file(file, metadata, ft_ext, mt_ext, transpose)
0
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104
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105 required_columns <- c("sampleName", "class", "sampleType", "injectionOrder")
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106 optional_columns <- c("batch")
2
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107
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108 data <- verify_input_dataframe(data, required_columns)
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109
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110 data <- sort_by_injection_order(data)
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111
2
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112 feature_columns <- colnames(data)[!colnames(data) %in%
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113 c(required_columns, optional_columns)]
0
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114 features <- data[, feature_columns]
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115 injection_order <- data$injectionOrder
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116
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117 # run WaveICA
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118 features <- recetox.waveica::waveica_nonbatchwise(
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119 data = features,
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120 wf = get_wf(wavelet_filter, wavelet_length),
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121 injection_order = injection_order,
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122 K = k,
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123 alpha = alpha,
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124 cutoff = cutoff
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125 )
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126
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127 data[, feature_columns] <- features
2
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128 group <- enumerate_groups(as.character(data$sampleType))
0
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129 # remove blanks from dataset
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130 if (exclude_blanks) {
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131 data <- exclude_group(data, group)
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132 }
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133
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134 return(data)
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135 }
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136
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137
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138 sort_by_injection_order <- function(data) {
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139 if ("batch" %in% colnames(data)) {
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140 data <- data[order(data[, "batch"],
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141 data[, "injectionOrder"],
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142 decreasing = FALSE
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143 ), ]
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144 } else {
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145 data <- data[order(data[, "injectionOrder"],
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146 decreasing = FALSE
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147 ), ]
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148 }
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149 return(data)
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150 }
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151
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152
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153 verify_input_dataframe <- function(data, required_columns) {
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154 if (anyNA(data)) {
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155 stop("Error: dataframe cannot contain NULL values!
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156 Make sure that your dataframe does not contain empty cells")
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157 } else if (!all(required_columns %in% colnames(data))) {
2
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158 stop(
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159 "Error: missing metadata!
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160 Make sure that the following columns are present in your dataframe: ",
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161 paste(required_columns, collapse = ", ")
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162 )
0
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163 }
2
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164
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165 data <- verify_column_types(data, required_columns)
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166
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167 return(data)
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168 }
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169
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170 verify_column_types <- function(data, required_columns) {
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171 # Specify the column names and their expected types
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172 column_types <- list(
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173 "sampleName" = c("character", "factor"),
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174 "class" = c("character", "factor"),
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175 "sampleType" = c("character", "factor"),
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176 "injectionOrder" = "integer",
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177 "batch" = "integer"
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178 )
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179
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180 column_types <- column_types[required_columns]
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181
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182 for (col_name in names(data)) {
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183 actual_type <- class(data[[col_name]])
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184 if (col_name %in% names(column_types)) {
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185 expected_types <- column_types[[col_name]]
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186
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187 if (!actual_type %in% expected_types) {
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188 stop(
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189 "Column ", col_name, " is of type ", actual_type,
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190 " but expected type is ",
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191 paste(expected_types, collapse = " or "), "\n"
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192 )
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193 }
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194 } else {
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195 if (actual_type != "numeric") {
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196 data[[col_name]] <- as.numeric(as.character(data[[col_name]]))
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197 }
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198 }
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199 }
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200 return(data)
0
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201 }
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202
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203
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204 # Match group labels with [blank/sample/qc] and enumerate them
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205 enumerate_groups <- function(group) {
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206 group[grepl("blank", tolower(group))] <- 0
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207 group[grepl("sample", tolower(group))] <- 1
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208 group[grepl("qc", tolower(group))] <- 2
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209
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210 return(group)
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211 }
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212
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213
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214 # Create appropriate input for R wavelets function
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215 get_wf <- function(wavelet_filter, wavelet_length) {
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216 wf <- paste(wavelet_filter, wavelet_length, sep = "")
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217
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218 # exception to the wavelet function
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219 if (wf == "d2") {
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220 wf <- "haar"
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221 }
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222
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223 return(wf)
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224 }
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225
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226
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227 # Exclude blanks from a dataframe
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228 exclude_group <- function(data, group) {
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229 row_idx_to_exclude <- which(group %in% 0)
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230 if (length(row_idx_to_exclude) > 0) {
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231 data_without_blanks <- data[-c(row_idx_to_exclude), ]
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232 cat("Blank samples have been excluded from the dataframe.\n")
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233 return(data_without_blanks)
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234 } else {
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235 return(data)
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236 }
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237 }
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238
1
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239 store_data <- function(data, output, ext) {
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240 if (ext == "csv") {
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241 write.csv(data, file = output, row.names = FALSE, quote = FALSE)
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242 } else if (ext == "tsv") {
2
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243 write.table(data,
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244 file = output, sep = "\t",
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245 row.names = FALSE, quote = FALSE
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246 )
1
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247 } else {
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248 arrow::write_parquet(data, sink = output)
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249 }
0
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250 cat("Normalization has been completed.\n")
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251 }