Mercurial > repos > recetox > recetox_aplcms_recover_weaker_signals

annotate main.R @ 1:880dc35a48c2 draft

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 699355cdf45b2157e9eea3962a01950d469fb0ba
author recetox
date Thu, 16 Jun 2022 10:23:42 +0000
parents f8f6095377be
children
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f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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1 library(recetox.aplcms)
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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2 library(dplyr)
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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4 save_extracted_features <- function(df, filename) {
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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5 df <- as.data.frame(df)
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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6 columns <- c("mz", "pos", "sd1", "sd2", "area")
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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7 arrow::write_parquet(df[columns], filename)
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8 }
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10 save_aligned_feature_table <- function(df, filename) {
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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11 columns <- c("feature", "mz", "rt", "sample", "sample_rt", "sample_intensity")
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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12 arrow::write_parquet(df[columns], filename)
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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13 }
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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15 save_recovered_feature_table <- function(df, filename, out_format) {
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16 columns <- c("feature", "mz", "rt", "sample", "sample_rt", "sample_intensity")
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17 if (out_format == "recetox") {
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18 peak_table <- df[columns]
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19 recetox_peak_table <- rcx_aplcms_to_rcx_xmsannotator(peak_table)
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20 arrow::write_parquet(recetox_peak_table, filename)
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21 } else {
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22 arrow::write_parquet(df[columns], filename)
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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23 }
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24 }
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26 rcx_aplcms_to_rcx_xmsannotator <- function(peak_table) {
f8f6095377be planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 19de0924a65bc65cbbf7c1fc17e9b5348305f95c
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27 col_base <- c("feature", "mz", "rt")
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28 output_table <- peak_table %>% distinct(across(any_of(col_base)))
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30 for (level in levels(factor(peak_table$sample))) {
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31 subdata <- peak_table %>%
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32 filter(sample == level) %>%
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33 select(any_of(c(col_base, "sample_intensity"))) %>%
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34 rename(!!level := "sample_intensity")
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35 output_table <- inner_join(output_table, subdata, by = col_base)
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36 }
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37 output_table <- output_table %>% rename(peak = feature)
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38 return(output_table)
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39 }
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41 known_table_columns <- function() {
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42 c("chemical_formula", "HMDB_ID", "KEGG_compound_ID", "mass", "ion.type",
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43 "m.z", "Number_profiles_processed", "Percent_found", "mz_min", "mz_max",
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44 "RT_mean", "RT_sd", "RT_min", "RT_max", "int_mean(log)", "int_sd(log)",
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45 "int_min(log)", "int_max(log)")
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46 }
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47
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48 save_known_table <- function(df, filename) {
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49 columns <- known_table_columns()
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50 arrow::write_parquet(df[columns], filename)
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51 }
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52
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53 read_known_table <- function(filename) {
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54 arrow::read_parquet(filename, col_select = known_table_columns())
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55 }
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57 save_pairing <- function(df, filename) {
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58 write.table(df, filename, row.names = FALSE, col.names = c("new", "old"))
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59 }
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61 save_all_extracted_features <- function(dfs, filenames) {
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62 filenames <- tools::file_path_sans_ext(basename(filenames))
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63 filenames <- paste0(filenames, ".parquet")
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64 filenames <- file.path("extracted", filenames)
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65 dir.create("extracted")
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66 mapply(save_extracted_features, dfs, filenames)
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67 }
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69 save_all_corrected_features <- function(dfs, filenames) {
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70 filenames <- tools::file_path_sans_ext(basename(filenames))
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71 filenames <- paste0(filenames, ".parquet")
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72 filenames <- file.path("corrected", filenames)
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73 dir.create("corrected")
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74 mapply(save_extracted_features, dfs, filenames)
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75 }
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77 unsupervised_main <- function(sample_files, aligned_file, recovered_file, out_format, ...) {
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78 sample_files <- sort_samples_by_acquisition_number(sample_files)
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80 res <- unsupervised(filenames = sample_files, ...)
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82 save_all_features(res, sample_files)
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83 save_all_feature_tables(res$aligned_feature_sample_table, res$recovered_feature_sample_table, aligned_file, recovered_file, out_format)
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84 }
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86 hybrid_main <- function(sample_files, known_table_file, updated_known_table_file, pairing_file, aligned_file, recovered_file, out_format, ...) {
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87 sample_files <- sort_samples_by_acquisition_number(sample_files)
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88
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89 known <- read_known_table(known_table_file)
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90 res <- hybrid(filenames = sample_files, known_table = known, ...)
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91
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92 save_known_table(res$updated_known_table, updated_known_table_file)
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93 save_pairing(res$features_known_table_pairing, pairing_file)
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94
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95 save_all_features(res, sample_files)
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96 save_all_feature_tables(res$aligned_feature_sample_table, res$recovered_feature_sample_table, aligned_file, recovered_file, out_format)
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97 }
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98
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99 save_all_features <- function(result, sample_files) {
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100 save_all_extracted_features(result$extracted_features, sample_files)
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101 save_all_corrected_features(result$corrected_features, sample_files)
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102 }
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103
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104 save_all_feature_tables <- function(aligned_feature_sample_table,
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105 recovered_feature_sample_table,
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106 aligned_file,
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107 recovered_file,
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108 out_format) {
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109 save_aligned_feature_table(aligned_feature_sample_table, aligned_file)
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110 save_recovered_feature_table(recovered_feature_sample_table, recovered_file, out_format)
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111 }
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112
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113 two_step_hybrid_main <- function(sample_files, known_table_file, updated_known_table_file, recovered_file, aligned_file, out_format, metadata, ...) {
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114 sample_files <- sort_samples_by_acquisition_number(sample_files)
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115 metadata <- read.table(metadata, sep = ",", header = TRUE)
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116
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117 known_table <- read_known_table(known_table_file)
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118 res <- two.step.hybrid(filenames = sample_files, known.table = known_table, work_dir = getwd(), metadata = metadata, ...)
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119
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120 save_known_table(res$known_table, updated_known_table_file)
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121 save_aligned_feature_table(res$aligned_features, aligned_file)
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122 save_recovered_feature_table(res$final_features, recovered_file, out_format)
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123 }