Mercurial > repos > recetox > recetox_aplcms_recover_weaker_signals

annotate utils.R @ 6:e2cb970d99dd draft

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 775afc79d12e680bb26496a2626d1855db9cddc7
author recetox
date Thu, 25 May 2023 12:10:23 +0000
parents fd66fc063ce8
children 99d118321d5f
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067a308223e3 planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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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 load_sample_name <- function(df) {
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20 sample_name <- attr(df, "sample_name")
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21 if (is.null(sample_name)) {
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22 return(NA)
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23 } else {
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24 return(sample_name)
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25 }
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26 }
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28 save_data_as_parquet_file <- function(data, filename) {
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29 arrow::write_parquet(data, filename)
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30 }
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32 load_data_from_parquet_file <- function(filename) {
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33 return(arrow::read_parquet(filename))
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34 }
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36 load_parquet_collection <- function(files) {
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37 features <- lapply(files, arrow::read_parquet)
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38 features <- lapply(features, tibble::as_tibble)
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39 return(features)
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40 }
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42 save_parquet_collection <- function(feature_tables, sample_names, subdir) {
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43 dir.create(subdir)
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44 for (i in seq_len(length(feature_tables))) {
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45 filename <- file.path(subdir, paste0(sample_names[i], ".parquet"))
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46 feature_table <- as.data.frame(feature_tables[[i]])
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47 feature_table <- save_sample_name(feature_table, sample_names[i])
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48 arrow::write_parquet(feature_table, filename)
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49 }
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50 }
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52 sort_by_sample_name <- function(tables, sample_names) {
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53 return(tables[order(sample_names)])
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54 }
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56 save_tolerances <- function(table, tol_file) {
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57 mz_tolerance <- c(table$mz_tol_relative)
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58 rt_tolerance <- c(table$rt_tol_relative)
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59 arrow::write_parquet(data.frame(mz_tolerance, rt_tolerance), tol_file)
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60 }
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62 save_aligned_features <- function(aligned_features, metadata_file, rt_file, intensity_file) {
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63 save_data_as_parquet_file(aligned_features$metadata, metadata_file)
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64 save_data_as_parquet_file(aligned_features$rt, rt_file)
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65 save_data_as_parquet_file(aligned_features$intensity, intensity_file)
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66 }
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68 select_table_with_sample_name <- function(tables, sample_name) {
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69 sample_names <- lapply(tables, load_sample_name)
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70 index <- which(sample_names == sample_name)
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71 if (length(index) > 0) {
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72 return(tables[[index]])
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73 } else {
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74 stop(sprintf("Mismatch - sample name '%s' not present in %s",
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75 sample_name, paste(sample_names, collapse = ", ")))
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76 }
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77 }
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79 select_adjusted <- function(recovered_features) {
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80 return(recovered_features$adjusted_features)
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81 }
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83 known_table_columns <- function() {
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84 c("chemical_formula", "HMDB_ID", "KEGG_compound_ID", "mass", "ion.type",
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85 "m.z", "Number_profiles_processed", "Percent_found", "mz_min", "mz_max",
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86 "RT_mean", "RT_sd", "RT_min", "RT_max", "int_mean(log)", "int_sd(log)",
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87 "int_min(log)", "int_max(log)")
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88 }
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89
2
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90 save_known_table <- function(table, filename) {
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91 columns <- known_table_columns()
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92 arrow::write_parquet(table$known_table[columns], filename)
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93 }
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94
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95 read_known_table <- function(filename) {
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96 arrow::read_parquet(filename, col_select = known_table_columns())
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97 }
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98
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99 save_pairing <- function(table, filename) {
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100 df <- table$pairing %>% as_tibble() %>% setNames(c("new", "old"))
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101 arrow::write_parquet(df, filename)
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102 }
2
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103
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104 join_tables_to_list <- function(metadata, rt_table, intensity_table) {
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105 features <- new("list")
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106 features$metadata <- metadata
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107 features$intensity <- intensity_table
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108 features$rt <- rt_table
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109 return(features)
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110 }
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111
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112 validate_sample_names <- function(sample_names) {
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113 if ((any(is.na(sample_names))) || (length(unique(sample_names)) != length(sample_names))) {
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114 stop(sprintf("Sample names absent or not unique - provided sample names: %s",
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115 paste(sample_names, collapse = ", ")))
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116 }
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117 }
3
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118
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119 determine_sigma_ratios <- function(sigma_ratio_lim_min = NA, sigma_ratio_lim_max = NA) {
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120 if (is.na(sigma_ratio_lim_min)) {
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121 sigma_ratio_lim_min <- 0
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122 }
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123 if (is.na(sigma_ratio_lim_max)) {
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124 sigma_ratio_lim_max <- Inf
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125 }
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126 return(c(sigma_ratio_lim_min, sigma_ratio_lim_max))
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127 }