Mercurial > repos > recetox > waveica

annotate waveica_wrapper.R @ 4:8b55efc7d117 draft

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"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/waveica commit aa8206a01efc1813f2586584782f28a73a17fe86"
author recetox
date Mon, 10 Jan 2022 16:01:35 +0000
parents d08deef1eb44
children cf3f2f964d80
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1 waveica <- function(data,
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2 wavelet_filter,
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3 wavelet_length,
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4 k,
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5 t,
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6 t2,
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7 alpha,
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8 exclude_blanks) {
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10 # get input from the Galaxy, preprocess data
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11 data <- read.csv(data, header = TRUE)
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13 required_columns <- c("sampleName", "class", "sampleType", "injectionOrder", "batch")
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14 verify_input_dataframe(data, required_columns)
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16 data <- sort_by_injection_order(data)
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18 # separate data into features, batch and group
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19 feature_columns <- colnames(data)[!colnames(data) %in% required_columns]
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20 features <- data[, feature_columns]
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21 group <- enumerate_groups(as.character(data$sampleType))
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22 batch <- data$batch
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24 # run WaveICA
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25 features <- recetox.waveica::waveica(
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26 data = features,
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27 wf = get_wf(wavelet_filter, wavelet_length),
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28 batch = batch,
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29 group = group,
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30 K = k,
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31 t = t,
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32 t2 = t2,
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33 alpha = alpha
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34 )
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36 data[, feature_columns] <- features
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38 # remove blanks from dataset
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39 if (exclude_blanks) {
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40 data <- exclude_group(data, group)
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41 }
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43 return(data)
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44 }
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47 waveica_singlebatch <- function(data,
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48 wavelet_filter,
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49 wavelet_length,
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50 k,
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51 alpha,
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52 cutoff,
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53 exclude_blanks) {
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55 # get input from the Galaxy, preprocess data
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56 data <- read.csv(data, header = TRUE)
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58 required_columns <- c("sampleName", "class", "sampleType", "injectionOrder")
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59 optional_columns <- c("batch")
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60 verify_input_dataframe(data, required_columns)
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62 data <- sort_by_injection_order(data)
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64 feature_columns <- colnames(data)[!colnames(data) %in% c(required_columns, optional_columns)]
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65 features <- data[, feature_columns]
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66 injection_order <- data$injectionOrder
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68 # run WaveICA
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69 features <- recetox.waveica::waveica_nonbatchwise(
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70 data = features,
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71 wf = get_wf(wavelet_filter, wavelet_length),
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72 injection_order = injection_order,
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73 K = k,
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74 alpha = alpha,
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75 cutoff = cutoff
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76 )
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78 data[, feature_columns] <- features
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80 # remove blanks from dataset
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81 if (exclude_blanks) {
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82 data <- exclude_group(data, group)
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83 }
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85 return(data)
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86 }
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89 sort_by_injection_order <- function(data) {
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90 if ("batch" %in% colnames(data)) {
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91 data <- data[order(data[, "batch"],
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92 data[, "injectionOrder"],
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93 decreasing = FALSE
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94 ), ]
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95 } else {
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96 data <- data[order(data[, "injectionOrder"],
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97 decreasing = FALSE
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98 ), ]
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99 }
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100 return(data)
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101 }
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102
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103
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104 verify_input_dataframe <- function(data, required_columns) {
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105 if (anyNA(data)) {
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106 stop("Error: dataframe cannot contain NULL values!
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107 Make sure that your dataframe does not contain empty cells")
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108 } else if (!all(required_columns %in% colnames(data))) {
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109 stop("Error: missing metadata!
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110 Make sure that the following columns are present in your dataframe: ", paste(required_columns, collapse = ", "))
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111 }
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112 }
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113
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114
1
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115 # Match group labels with [blank/sample/qc] and enumerate them
2
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116 enumerate_groups <- function(group) {
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117 group[grepl("blank", tolower(group))] <- 0
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118 group[grepl("sample", tolower(group))] <- 1
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119 group[grepl("qc", tolower(group))] <- 2
0
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120
2
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121 return(group)
0
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122 }
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123
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124
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125 # Create appropriate input for R wavelets function
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126 get_wf <- function(wavelet_filter, wavelet_length) {
2
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127 wf <- paste(wavelet_filter, wavelet_length, sep = "")
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128
2
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129 # exception to the wavelet function
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130 if (wf == "d2") {
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131 wf <- "haar"
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132 }
0
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133
2
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134 return(wf)
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135 }
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136
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137
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138 # Exclude blanks from a dataframe
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139 exclude_group <- function(data, group) {
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140 row_idx_to_exclude <- which(group %in% 0)
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141 if (length(row_idx_to_exclude) > 0) {
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142 data_without_blanks <- data[-c(row_idx_to_exclude), ]
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143 cat("Blank samples have been excluded from the dataframe.\n")
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144 return(data_without_blanks)
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145 } else {
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146 return(data)
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147 }
0
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148 }
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149
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150
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151 # Store output of WaveICA in a tsv file
2
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152 store_data <- function(data, output) {
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153 write.table(data, file = output, sep = "\t", row.names = FALSE, quote = FALSE)
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154 cat("Normalization has been completed.\n")
0
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155 }