# HG changeset patch
# User recetox
# Date 1697023162 0
# Node ID 12bf74dd09f1f51bcd1b67feb2d456d4769071fc
# Parent d90187b0f2472cf58acd7bf594ac2f982859b2e5
planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 97249a1af94ac5c387e1ede274dec5364f71cde9
diff -r d90187b0f247 -r 12bf74dd09f1 macros.xml
--- a/macros.xml Wed Jul 19 00:26:32 2023 +0000
+++ b/macros.xml Wed Oct 11 11:19:22 2023 +0000
@@ -13,6 +13,9 @@
topic_0091
topic_3520
+
+
+
recetox-aplcms
@@ -81,14 +84,18 @@
help="The upper limit of the ratio range between the left-standard deviation and the right-standard deviation of the bi-Gaussian function to fit the data." />
-
+
+
+
+
+
+
diff -r d90187b0f247 -r 12bf74dd09f1 recetox_aplcms_remove_noise.xml
--- a/recetox_aplcms_remove_noise.xml Wed Jul 19 00:26:32 2023 +0000
+++ b/recetox_aplcms_remove_noise.xml Wed Oct 11 11:19:22 2023 +0000
@@ -1,13 +1,14 @@
-
+
filter noise and detect peaks in high resolution mass spectrometry (HRMS) profile data
macros.xml
help.xml
+
operation_3937
-
+
diff -r d90187b0f247 -r 12bf74dd09f1 test-data/peak_table_galaxy.parquet
Binary file test-data/peak_table_galaxy.parquet has changed
diff -r d90187b0f247 -r 12bf74dd09f1 utils.R
--- a/utils.R Wed Jul 19 00:26:32 2023 +0000
+++ b/utils.R Wed Oct 11 11:19:22 2023 +0000
@@ -1,94 +1,98 @@
library(recetox.aplcms)
get_env_sample_name <- function() {
- sample_name <- Sys.getenv("SAMPLE_NAME", unset = NA)
- if (nchar(sample_name) == 0) {
- sample_name <- NA
- }
- if (is.na(sample_name)) {
- message("The mzML file does not contain run ID.")
- }
- return(sample_name)
+ sample_name <- Sys.getenv("SAMPLE_NAME", unset = NA)
+ if (nchar(sample_name) == 0) {
+ sample_name <- NA
+ }
+ if (is.na(sample_name)) {
+ message("The mzML file does not contain run ID.")
+ }
+ return(sample_name)
}
save_sample_name <- function(df, sample_name) {
- attr(df, "sample_name") <- sample_name
- return(df)
+ attr(df, "sample_name") <- sample_name
+ return(df)
}
restore_sample_name <- function(df) {
- return(df$sample_id[1])
+ return(df$sample_id[1])
}
load_sample_name <- function(df) {
- sample_name <- attr(df, "sample_name")
- if (is.null(sample_name)) {
- return(NA)
- } else {
- return(sample_name)
- }
+ sample_name <- attr(df, "sample_name")
+ if (is.null(sample_name)) {
+ return(NA)
+ } else {
+ return(sample_name)
+ }
}
save_data_as_parquet_file <- function(data, filename) {
- arrow::write_parquet(data, filename)
+ arrow::write_parquet(data, filename)
}
load_data_from_parquet_file <- function(filename) {
- return(arrow::read_parquet(filename))
+ return(arrow::read_parquet(filename))
}
load_parquet_collection <- function(files) {
- features <- lapply(files, arrow::read_parquet)
- features <- lapply(features, tibble::as_tibble)
- return(features)
+ features <- lapply(files, arrow::read_parquet)
+ features <- lapply(features, tibble::as_tibble)
+ return(features)
}
save_parquet_collection <- function(feature_tables, sample_names, subdir) {
- dir.create(subdir)
- for (i in seq_len(length(feature_tables))) {
- filename <- file.path(subdir, paste0(sample_names[i], ".parquet"))
- feature_table <- as.data.frame(feature_tables[[i]])
- feature_table <- save_sample_name(feature_table, sample_names[i])
- arrow::write_parquet(feature_table, filename)
- }
+ dir.create(subdir)
+ for (i in seq_len(length(feature_tables))) {
+ filename <- file.path(subdir, paste0(sample_names[i], ".parquet"))
+ feature_table <- as.data.frame(feature_tables[[i]])
+ feature_table <- save_sample_name(feature_table, sample_names[i])
+ arrow::write_parquet(feature_table, filename)
+ }
}
sort_by_sample_name <- function(tables, sample_names) {
- return(tables[order(sample_names)])
+ return(tables[order(sample_names)])
}
save_tolerances <- function(table, tol_file) {
- mz_tolerance <- c(table$mz_tol_relative)
- rt_tolerance <- c(table$rt_tol_relative)
- arrow::write_parquet(data.frame(mz_tolerance, rt_tolerance), tol_file)
+ mz_tolerance <- c(table$mz_tol_relative)
+ rt_tolerance <- c(table$rt_tol_relative)
+ arrow::write_parquet(data.frame(mz_tolerance, rt_tolerance), tol_file)
}
save_aligned_features <- function(aligned_features, metadata_file, rt_file, intensity_file) {
- save_data_as_parquet_file(aligned_features$metadata, metadata_file)
- save_data_as_parquet_file(aligned_features$rt, rt_file)
- save_data_as_parquet_file(aligned_features$intensity, intensity_file)
+ save_data_as_parquet_file(aligned_features$metadata, metadata_file)
+ save_data_as_parquet_file(aligned_features$rt, rt_file)
+ save_data_as_parquet_file(aligned_features$intensity, intensity_file)
}
select_table_with_sample_name <- function(tables, sample_name) {
- sample_names <- lapply(tables, load_sample_name)
- index <- which(sample_names == sample_name)
- if (length(index) > 0) {
- return(tables[[index]])
- } else {
- stop(sprintf("Mismatch - sample name '%s' not present in %s",
- sample_name, paste(sample_names, collapse = ", ")))
- }
+ sample_names <- lapply(tables, load_sample_name)
+ index <- which(sample_names == sample_name)
+ if (length(index) > 0) {
+ return(tables[[index]])
+ } else {
+ stop(sprintf(
+ "Mismatch - sample name '%s' not present in %s",
+ sample_name, paste(sample_names, collapse = ", ")
+ ))
+ }
}
select_adjusted <- function(recovered_features) {
- return(recovered_features$adjusted_features)
+ return(recovered_features$adjusted_features)
}
known_table_columns <- function() {
- c("chemical_formula", "HMDB_ID", "KEGG_compound_ID", "mass", "ion.type",
+ 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)")
+ "int_min(log)", "int_max(log)"
+ )
}
save_known_table <- function(table, filename) {
@@ -101,7 +105,9 @@
}
save_pairing <- function(table, filename) {
- df <- table$pairing %>% as_tibble() %>% setNames(c("new", "old"))
+ df <- table$pairing %>%
+ as_tibble() %>%
+ setNames(c("new", "old"))
arrow::write_parquet(df, filename)
}
@@ -114,18 +120,20 @@
}
validate_sample_names <- function(sample_names) {
- if ((any(is.na(sample_names))) || (length(unique(sample_names)) != length(sample_names))) {
- stop(sprintf("Sample names absent or not unique - provided sample names: %s",
- paste(sample_names, collapse = ", ")))
- }
+ if ((any(is.na(sample_names))) || (length(unique(sample_names)) != length(sample_names))) {
+ stop(sprintf(
+ "Sample names absent or not unique - provided sample names: %s",
+ paste(sample_names, collapse = ", ")
+ ))
+ }
}
determine_sigma_ratios <- function(sigma_ratio_lim_min = NA, sigma_ratio_lim_max = NA) {
- if (is.na(sigma_ratio_lim_min)) {
- sigma_ratio_lim_min <- 0
- }
- if (is.na(sigma_ratio_lim_max)) {
- sigma_ratio_lim_max <- Inf
- }
- return(c(sigma_ratio_lim_min, sigma_ratio_lim_max))
+ if (is.na(sigma_ratio_lim_min)) {
+ sigma_ratio_lim_min <- 0
+ }
+ if (is.na(sigma_ratio_lim_max)) {
+ sigma_ratio_lim_max <- Inf
+ }
+ return(c(sigma_ratio_lim_min, sigma_ratio_lim_max))
}