# HG changeset patch # User recetox # Date 1684939775 0 # Node ID 353b9d58d3604292b5dd8223285770546a04c0a5 # Parent 7b0bf5d403ba148c5708156241163ba3c5756998 planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/recetox_aplcms commit 724ecb1b81ebd8a67488b8a9397177b2ff0357db diff -r 7b0bf5d403ba -r 353b9d58d360 help.xml --- a/help.xml Mon Apr 03 14:56:27 2023 +0000 +++ b/help.xml Wed May 24 14:49:35 2023 +0000 @@ -110,7 +110,6 @@ ================================= Group features with `mz` and `rt` using tolerances within the tolerance into clusters, creating larger features from raw data points. -Custom tolerances for `mz` and `rt` are computed based on the given parameters. The tool takes a collection of all detected features and computes the clusters over a global feature table, adding the `sample_id` and `cluster` columns to the table. Example Output @@ -133,7 +132,7 @@ recetox-aplcms - correct time ============================= -Apply spline-based retention time correction to a feature table given the template table and the computed `mz` and `rt` tolerances. +Apply spline-based retention time correction to a feature table given the template table and the `mz` and `rt` tolerances. Example Output -------------- diff -r 7b0bf5d403ba -r 353b9d58d360 macros.xml --- a/macros.xml Mon Apr 03 14:56:27 2023 +0000 +++ b/macros.xml Wed May 24 14:49:35 2023 +0000 @@ -1,5 +1,5 @@ - 0.10.3 + 0.11.0 r-recetox-aplcms @@ -93,32 +93,11 @@ - - - - - - - - - - - - - - - - - + + + diff -r 7b0bf5d403ba -r 353b9d58d360 recetox_aplcms_correct_time.xml --- a/recetox_aplcms_correct_time.xml Mon Apr 03 14:56:27 2023 +0000 +++ b/recetox_aplcms_correct_time.xml Wed May 24 14:49:35 2023 +0000 @@ -20,13 +20,12 @@ } template_features <- load_data_from_parquet_file('$template') - tolerances <- load_data_from_parquet_file('$tolerances') corrected_table <- correct_time( this.feature = features_table, template_features = template_features, - mz_tol_relative = get_mz_tol(tolerances), - rt_tol_relative = get_rt_tol(tolerances) + mz_tol_relative = $mz_tol_relative_ppm * 1e-06, + rt_tol_relative = $rt_tol ) corrected_table <- save_sample_name(corrected_table, sample_name) @@ -39,8 +38,7 @@ help="Mass spectrometry clustered features table." /> - + diff -r 7b0bf5d403ba -r 353b9d58d360 test-data/remove_noise_docker.parquet Binary file test-data/remove_noise_docker.parquet has changed diff -r 7b0bf5d403ba -r 353b9d58d360 utils.R --- a/utils.R Mon Apr 03 14:56:27 2023 +0000 +++ b/utils.R Wed May 24 14:49:35 2023 +0000 @@ -39,11 +39,11 @@ return(features) } -save_parquet_collection <- function(table, sample_names, subdir) { +save_parquet_collection <- function(feature_tables, sample_names, subdir) { dir.create(subdir) - for (i in seq_len(length(table$feature_tables))) { + for (i in seq_len(length(feature_tables))) { filename <- file.path(subdir, paste0(subdir, "_", sample_names[i], ".parquet")) - feature_table <- as.data.frame(table$feature_tables[[i]]) + feature_table <- as.data.frame(feature_tables[[i]]) feature_table <- save_sample_name(feature_table, sample_names[i]) arrow::write_parquet(feature_table, filename) } @@ -59,14 +59,6 @@ arrow::write_parquet(data.frame(mz_tolerance, rt_tolerance), tol_file) } -get_mz_tol <- function(tolerances) { - return(tolerances$mz_tolerance) -} - -get_rt_tol <- function(tolerances) { - return(tolerances$rt_tolerance) -} - save_aligned_features <- function(aligned_features, metadata_file, rt_file, intensity_file) { save_data_as_parquet_file(aligned_features$metadata, metadata_file) save_data_as_parquet_file(aligned_features$rt, rt_file)