Mercurial > repos > recetox > recetox_aplcms_recover_weaker_signals

annotate utils.R @ 8:99d118321d5f draft

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 0873c036d734782d2647b0eea84cd1a0658f5e58
author recetox
date Wed, 19 Jul 2023 00:27:52 +0000
parents e2cb970d99dd
children a9bb2ccc53de
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1 library(recetox.aplcms)
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3 get_env_sample_name <- function() {
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4 sample_name <- Sys.getenv("SAMPLE_NAME", unset = NA)
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5 if (nchar(sample_name) == 0) {
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6 sample_name <- NA
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7 }
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8 if (is.na(sample_name)) {
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9 message("The mzML file does not contain run ID.")
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10 }
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11 return(sample_name)
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12 }
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14 save_sample_name <- function(df, sample_name) {
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15 attr(df, "sample_name") <- sample_name
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16 return(df)
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17 }
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19 restore_sample_name <- function(df) {
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20 return(df$sample_id[1])
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21 }
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23 load_sample_name <- function(df) {
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24 sample_name <- attr(df, "sample_name")
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25 if (is.null(sample_name)) {
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26 return(NA)
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27 } else {
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28 return(sample_name)
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29 }
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30 }
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32 save_data_as_parquet_file <- function(data, filename) {
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33 arrow::write_parquet(data, filename)
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34 }
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36 load_data_from_parquet_file <- function(filename) {
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37 return(arrow::read_parquet(filename))
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38 }
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40 load_parquet_collection <- function(files) {
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41 features <- lapply(files, arrow::read_parquet)
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42 features <- lapply(features, tibble::as_tibble)
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43 return(features)
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44 }
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46 save_parquet_collection <- function(feature_tables, sample_names, subdir) {
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47 dir.create(subdir)
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48 for (i in seq_len(length(feature_tables))) {
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49 filename <- file.path(subdir, paste0(sample_names[i], ".parquet"))
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50 feature_table <- as.data.frame(feature_tables[[i]])
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51 feature_table <- save_sample_name(feature_table, sample_names[i])
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52 arrow::write_parquet(feature_table, filename)
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53 }
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54 }
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56 sort_by_sample_name <- function(tables, sample_names) {
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57 return(tables[order(sample_names)])
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58 }
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60 save_tolerances <- function(table, tol_file) {
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61 mz_tolerance <- c(table$mz_tol_relative)
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62 rt_tolerance <- c(table$rt_tol_relative)
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63 arrow::write_parquet(data.frame(mz_tolerance, rt_tolerance), tol_file)
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64 }
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66 save_aligned_features <- function(aligned_features, metadata_file, rt_file, intensity_file) {
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67 save_data_as_parquet_file(aligned_features$metadata, metadata_file)
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68 save_data_as_parquet_file(aligned_features$rt, rt_file)
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69 save_data_as_parquet_file(aligned_features$intensity, intensity_file)
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70 }
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72 select_table_with_sample_name <- function(tables, sample_name) {
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73 sample_names <- lapply(tables, load_sample_name)
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74 index <- which(sample_names == sample_name)
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75 if (length(index) > 0) {
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76 return(tables[[index]])
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77 } else {
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78 stop(sprintf("Mismatch - sample name '%s' not present in %s",
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79 sample_name, paste(sample_names, collapse = ", ")))
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80 }
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81 }
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83 select_adjusted <- function(recovered_features) {
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84 return(recovered_features$adjusted_features)
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85 }
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87 known_table_columns <- function() {
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88 c("chemical_formula", "HMDB_ID", "KEGG_compound_ID", "mass", "ion.type",
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89 "m.z", "Number_profiles_processed", "Percent_found", "mz_min", "mz_max",
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90 "RT_mean", "RT_sd", "RT_min", "RT_max", "int_mean(log)", "int_sd(log)",
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91 "int_min(log)", "int_max(log)")
0
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92 }
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93
2
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94 save_known_table <- function(table, filename) {
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95 columns <- known_table_columns()
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96 arrow::write_parquet(table$known_table[columns], filename)
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97 }
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98
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99 read_known_table <- function(filename) {
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100 arrow::read_parquet(filename, col_select = known_table_columns())
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101 }
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102
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103 save_pairing <- function(table, filename) {
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104 df <- table$pairing %>% as_tibble() %>% setNames(c("new", "old"))
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105 arrow::write_parquet(df, filename)
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106 }
2
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107
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108 join_tables_to_list <- function(metadata, rt_table, intensity_table) {
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109 features <- new("list")
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110 features$metadata <- metadata
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111 features$intensity <- intensity_table
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112 features$rt <- rt_table
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113 return(features)
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114 }
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115
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116 validate_sample_names <- function(sample_names) {
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117 if ((any(is.na(sample_names))) || (length(unique(sample_names)) != length(sample_names))) {
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118 stop(sprintf("Sample names absent or not unique - provided sample names: %s",
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119 paste(sample_names, collapse = ", ")))
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120 }
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121 }
3
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122
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123 determine_sigma_ratios <- function(sigma_ratio_lim_min = NA, sigma_ratio_lim_max = NA) {
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124 if (is.na(sigma_ratio_lim_min)) {
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125 sigma_ratio_lim_min <- 0
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126 }
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127 if (is.na(sigma_ratio_lim_max)) {
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128 sigma_ratio_lim_max <- Inf
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129 }
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130 return(c(sigma_ratio_lim_min, sigma_ratio_lim_max))
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131 }