comparison main.R @ 0:c67f0eb6a909 draft

planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit b3e0c34f12c9c38fb34bf48197974620d60b50c5

0:c67f0eb6a909

library(recetox.aplcms)
library(dplyr)

save_extracted_features <- function(df, filename) {
  df <- as.data.frame(df)
  columns <- c("mz", "pos", "sd1", "sd2", "area")
  arrow::write_parquet(df[columns], filename)
}

save_aligned_feature_table <- function(df, filename) {
  columns <- c("feature", "mz", "rt", "sample", "sample_rt", "sample_intensity")
  arrow::write_parquet(df[columns], filename)
}

save_recovered_feature_table <- function(df, filename, out_format) {
  columns <- c("feature", "mz", "rt", "sample", "sample_rt", "sample_intensity")
  if (out_format == "recetox") {
    peak_table <- df[columns]
    recetox_peak_table <- rcx_aplcms_to_rcx_xmsannotator(peak_table)
    arrow::write_parquet(recetox_peak_table, filename)
  } else {
    arrow::write_parquet(df[columns], filename)
  }
}

rcx_aplcms_to_rcx_xmsannotator <- function(peak_table) {
    col_base <- c("feature", "mz", "rt")
    output_table <- peak_table %>% distinct(across(any_of(col_base)))

    for (level in levels(factor(peak_table$sample))) {
        subdata <- peak_table %>%
            filter(sample == level) %>%
            select(any_of(c(col_base, "sample_intensity"))) %>%
            rename(!!level := "sample_intensity")
        output_table <- inner_join(output_table, subdata, by = col_base)
    }
    output_table <- output_table %>% rename(peak = feature)
    return(output_table)
}

known_table_columns <- function() {
  c("chemical_formula", "HMDB_ID", "KEGG_compound_ID", "mass", "ion.type",
    "m.z", "Number_profiles_processed", "Percent_found", "mz_min", "mz_max",
    "RT_mean", "RT_sd", "RT_min", "RT_max", "int_mean(log)", "int_sd(log)",
    "int_min(log)", "int_max(log)")
}

save_known_table <- function(df, filename) {
  columns <- known_table_columns()
  arrow::write_parquet(df[columns], filename)
}

read_known_table <- function(filename) {
  arrow::read_parquet(filename, col_select = known_table_columns())
}

save_pairing <- function(df, filename) {
  write.table(df, filename, row.names = FALSE, col.names = c("new", "old"))
}

save_all_extracted_features <- function(dfs, filenames) {
  filenames <- tools::file_path_sans_ext(basename(filenames))
  filenames <- paste0(filenames, ".parquet")
  filenames <- file.path("extracted", filenames)
  dir.create("extracted")
  mapply(save_extracted_features, dfs, filenames)
}

save_all_corrected_features <- function(dfs, filenames) {
  filenames <- tools::file_path_sans_ext(basename(filenames))
  filenames <- paste0(filenames, ".parquet")
  filenames <- file.path("corrected", filenames)
  dir.create("corrected")
  mapply(save_extracted_features, dfs, filenames)
}

unsupervised_main <- function(sample_files, aligned_file, recovered_file, out_format, ...) {
  sample_files <- sort_samples_by_acquisition_number(sample_files)

  res <- unsupervised(filenames = sample_files, ...)

  save_all_extracted_features(res$extracted_features, sample_files)
  save_all_corrected_features(res$corrected_features, sample_files)

  save_aligned_feature_table(res$aligned_feature_sample_table, aligned_file)
  save_recovered_feature_table(res$recovered_feature_sample_table, recovered_file, out_format)
}

hybrid_main <- function(sample_files, known_table_file, updated_known_table_file, pairing_file, aligned_file, recovered_file, out_format, ...) {
  sample_files <- sort_samples_by_acquisition_number(sample_files)

  known <- read_known_table(known_table_file)
  res <- hybrid(filenames = sample_files, known_table = known, ...)

  save_known_table(res$updated_known_table, updated_known_table_file)
  save_pairing(res$features_known_table_pairing, pairing_file)

  save_all_extracted_features(res$extracted_features, sample_files)
  save_all_corrected_features(res$corrected_features, sample_files)

  save_aligned_feature_table(res$aligned_feature_sample_table, aligned_file)
  save_recovered_feature_table(res$recovered_feature_sample_table, recovered_file, out_format)
}

two_step_hybrid_main <- function(sample_files, known_table_file, updated_known_table_file, recovered_file, aligned_file, out_format, metadata, ...) {
  sample_files <- sort_samples_by_acquisition_number(sample_files)
  metadata <- read.table(metadata, sep = ",", header = TRUE)

  known_table <- read_known_table(known_table_file)
  res <- two.step.hybrid(filenames = sample_files, known.table = known_table, work_dir = getwd(), metadata = metadata, ...)

  save_known_table(res$known_table, updated_known_table_file)
  save_aligned_feature_table(res$aligned_features, aligned_file)
  save_recovered_feature_table(res$final_features, recovered_file, out_format)
}