Mercurial > repos > recetox > ramclustr

changeset 11:da7722f665f4 draft default tip

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/ramclustr commit bc3445f7c41271b0062c7674108f57708d08dd28
author recetox
date Thu, 30 May 2024 14:52:11 +0000
parents 2d94da58904b
children
files macros.xml ramclustr.xml ramclustr_wrapper.R
diffstat 3 files changed, 112 insertions(+), 109 deletions(-) [+]
line wrap: on
line diff
--- a/macros.xml	Wed May 22 08:04:21 2024 +0000
+++ b/macros.xml	Thu May 30 14:52:11 2024 +0000
@@ -66,7 +66,7 @@
     </xml>
 
     <xml name="parameters_recetox_aplcms">
-        <section name="ms_dataframe" title="Input MS Data as parquet (output from recetox-aplcms)" expanded="true">
+        <section name="ms_dataframe" title="Input MS Data as parquet/tabular (output from recetox-aplcms)" expanded="true">
             <param label="Input MS1 featureDefinitions" name="ms1_featureDefinitions" type="data" format="parquet,tabular"
                    help="Metadata with columns: mz, rt, feature names containing MS data."/>
             <param label="Input MS1 featureValues" name="ms1_featureValues" type="data" format="parquet,tabular"
--- a/ramclustr.xml	Wed May 22 08:04:21 2024 +0000
+++ b/ramclustr.xml	Thu May 30 14:52:11 2024 +0000
@@ -1,4 +1,4 @@
-<tool id="ramclustr" name="RAMClustR" version="@TOOL_VERSION@+galaxy6" profile="21.09">
+<tool id="ramclustr" name="RAMClustR" version="@TOOL_VERSION@+galaxy7" profile="21.09">
     <description>A feature clustering algorithm for non-targeted mass spectrometric metabolomics data.</description>
     <macros>
         <import>macros.xml</import>
--- a/ramclustr_wrapper.R	Wed May 22 08:04:21 2024 +0000
+++ b/ramclustr_wrapper.R	Thu May 30 14:52:11 2024 +0000
@@ -2,42 +2,42 @@
                          output_merge_msp,
                          output_spec_abundance,
                          msp_file) {
-  RAMClustR::write.msp(ramclustr_obj, one.file = output_merge_msp)
-  write.table(ramclustr_obj$SpecAbund,
-    file = output_spec_abundance,
-    row.names = TRUE, quote = FALSE, col.names = NA, sep = "\t"
-  )
+    RAMClustR::write.msp(ramclustr_obj, one.file = output_merge_msp)
+    write.table(ramclustr_obj$SpecAbund,
+        file = output_spec_abundance,
+        row.names = TRUE, quote = FALSE, col.names = NA, sep = "\t"
+    )
 
-  if (!is.null(msp_file)) {
-    exp_name <- ramclustr_obj$ExpDes[[1]][which(
-      row.names(ramclustr_obj$ExpDes[[1]]) == "Experiment"
-    ), 1]
-    filename <- paste("spectra/", exp_name, ".msp", sep = "")
-    file.copy(from = filename, to = msp_file, overwrite = TRUE)
-  }
+    if (!is.null(msp_file)) {
+        exp_name <- ramclustr_obj$ExpDes[[1]][which(
+            row.names(ramclustr_obj$ExpDes[[1]]) == "Experiment"
+        ), 1]
+        filename <- paste("spectra/", exp_name, ".msp", sep = "")
+        file.copy(from = filename, to = msp_file, overwrite = TRUE)
+    }
 }
 
 load_experiment_definition <- function(filename) {
-  experiment <- RAMClustR::defineExperiment(csv = filename)
-  return(experiment)
+    experiment <- RAMClustR::defineExperiment(csv = filename)
+    return(experiment)
 }
 
 read_metadata <- function(filename) {
-  data <- read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
+    data <- read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
 
-  if (!"qc" %in% colnames(data)) {
-    if ("sampleType" %in% colnames(data)) {
-      data$qc <- ifelse(data$sampleType == "qc", TRUE, FALSE)
+    if (!"qc" %in% colnames(data)) {
+        if ("sampleType" %in% colnames(data)) {
+            data$qc <- ifelse(data$sampleType == "qc", TRUE, FALSE)
+        }
     }
-  }
 
-  if (!"order" %in% colnames(data)) {
-    if ("injectionOrder" %in% colnames(data)) {
-      names(data)[names(data) == "injectionOrder"] <- "order"
+    if (!"order" %in% colnames(data)) {
+        if ("injectionOrder" %in% colnames(data)) {
+            names(data)[names(data) == "injectionOrder"] <- "order"
+        }
     }
-  }
 
-  return(data)
+    return(data)
 }
 
 read_ramclustr_aplcms <- function(ms1_featuredefinitions = NULL,
@@ -49,52 +49,55 @@
                                   ensure_no_na = TRUE,
                                   ms1_featuredefinitions_ext = "parquet",
                                   ms1_featurevalues_ext = "parquet") {
-  if (ms1_featuredefinitions_ext == "parquet") {
-    ms1_featuredefinitions <- arrow::read_parquet(ms1_featuredefinitions)
-  } else {
-    ms1_featuredefinitions <- read.csv(ms1_featuredefinitions,
-      header = TRUE, sep = "\t"
-    )
-  }
+    if (ms1_featuredefinitions_ext == "parquet") {
+        ms1_featuredefinitions <- arrow::read_parquet(ms1_featuredefinitions)
+    } else {
+        ms1_featuredefinitions <- read.csv(ms1_featuredefinitions,
+            header = TRUE, sep = "\t", check.names = FALSE
+        )
+    }
 
-  if (ms1_featurevalues_ext == "parquet") {
-    ms1_featurevalues <- arrow::read_parquet(ms1_featurevalues)
-  } else {
-    ms1_featurevalues <- read.csv(ms1_featurevalues, header = TRUE, sep = "\t")
-  }
-
-  if (!is.null(df_phenodata)) {
-    if (phenodata_ext == "csv") {
-      df_phenodata <- read.csv(
-        file = df_phenodata,
-        header = TRUE, check.names = FALSE
-      )
+    if (ms1_featurevalues_ext == "parquet") {
+        ms1_featurevalues <- arrow::read_parquet(ms1_featurevalues)
     } else {
-      df_phenodata <- read.csv(
-        file = df_phenodata,
-        header = TRUE, check.names = FALSE, sep = "\t"
-      )
+        ms1_featurevalues <- read.csv(ms1_featurevalues,
+            header = TRUE,
+            sep = "\t", check.names = FALSE
+        )
     }
-  }
-  if (!is.null(exp_des)) {
-    exp_des <- load_experiment_definition(exp_des)
-  }
 
-  feature_values <- ms1_featurevalues[-1]
-  feature_values <- t(feature_values)
-  colnames(feature_values) <- ms1_featurevalues[[1]]
-
-  feature_definitions <- data.frame(ms1_featuredefinitions)
+    if (!is.null(df_phenodata)) {
+        if (phenodata_ext == "csv") {
+            df_phenodata <- read.csv(
+                file = df_phenodata,
+                header = TRUE, check.names = FALSE
+            )
+        } else {
+            df_phenodata <- read.csv(
+                file = df_phenodata,
+                header = TRUE, check.names = FALSE, sep = "\t"
+            )
+        }
+    }
+    if (!is.null(exp_des)) {
+        exp_des <- load_experiment_definition(exp_des)
+    }
 
-  ramclustr_obj <- RAMClustR::rc.get.df.data(
-    ms1_featureDefinitions = feature_definitions,
-    ms1_featureValues = feature_values,
-    phenoData = df_phenodata,
-    ExpDes = exp_des,
-    st = st,
-    ensure.no.na = ensure_no_na
-  )
-  return(ramclustr_obj)
+    feature_values <- ms1_featurevalues[-1]
+    feature_values <- t(feature_values)
+    colnames(feature_values) <- ms1_featurevalues[[1]]
+
+    feature_definitions <- data.frame(ms1_featuredefinitions)
+
+    ramclustr_obj <- RAMClustR::rc.get.df.data(
+        ms1_featureDefinitions = feature_definitions,
+        ms1_featureValues = feature_values,
+        phenoData = df_phenodata,
+        ExpDes = exp_des,
+        st = st,
+        ensure.no.na = ensure_no_na
+    )
+    return(ramclustr_obj)
 }
 
 apply_normalisation <- function(ramclustr_obj = NULL,
@@ -104,49 +107,49 @@
                                 p_cut,
                                 rsq_cut,
                                 p_adjust) {
-  batch <- NULL
-  order <- NULL
-  qc <- NULL
+    batch <- NULL
+    order <- NULL
+    qc <- NULL
 
-  if (normalize_method == "TIC") {
-    ramclustr_obj <- RAMClustR::rc.feature.normalize.tic(
-      ramclustObj =
-        ramclustr_obj
-    )
-  } else if (normalize_method == "quantile") {
-    ramclustr_obj <- RAMClustR::rc.feature.normalize.quantile(ramclustr_obj)
-  } else if (normalize_method == "batch.qc") {
-    if (!(is.null(metadata_file) || metadata_file == "None")) {
-      metadata <- read_metadata(metadata_file)
-      batch <- metadata$batch
-      order <- metadata$order
-      qc <- metadata$qc
-    }
+    if (normalize_method == "TIC") {
+        ramclustr_obj <- RAMClustR::rc.feature.normalize.tic(
+            ramclustObj =
+                ramclustr_obj
+        )
+    } else if (normalize_method == "quantile") {
+        ramclustr_obj <- RAMClustR::rc.feature.normalize.quantile(ramclustr_obj)
+    } else if (normalize_method == "batch.qc") {
+        if (!(is.null(metadata_file) || metadata_file == "None")) {
+            metadata <- read_metadata(metadata_file)
+            batch <- metadata$batch
+            order <- metadata$order
+            qc <- metadata$qc
+        }
 
-    ramclustr_obj <- RAMClustR::rc.feature.normalize.batch.qc(
-      order = order,
-      batch = batch,
-      qc = qc,
-      ramclustObj = ramclustr_obj,
-      qc.inj.range = qc_inj_range
-    )
-  } else {
-    if (!(is.null(metadata_file) || metadata_file == "None")) {
-      metadata <- read_metadata(metadata_file)
-      batch <- metadata$batch
-      order <- metadata$order
-      qc <- metadata$qc
+        ramclustr_obj <- RAMClustR::rc.feature.normalize.batch.qc(
+            order = order,
+            batch = batch,
+            qc = qc,
+            ramclustObj = ramclustr_obj,
+            qc.inj.range = qc_inj_range
+        )
+    } else {
+        if (!(is.null(metadata_file) || metadata_file == "None")) {
+            metadata <- read_metadata(metadata_file)
+            batch <- metadata$batch
+            order <- metadata$order
+            qc <- metadata$qc
+        }
+
+        ramclustr_obj <- RAMClustR::rc.feature.normalize.qc(
+            order = order,
+            batch = batch,
+            qc = qc,
+            ramclustObj = ramclustr_obj,
+            p.cut = p_cut,
+            rsq.cut = rsq_cut,
+            p.adjust = p_adjust
+        )
     }
-
-    ramclustr_obj <- RAMClustR::rc.feature.normalize.qc(
-      order = order,
-      batch = batch,
-      qc = qc,
-      ramclustObj = ramclustr_obj,
-      p.cut = p_cut,
-      rsq.cut = rsq_cut,
-      p.adjust = p_adjust
-    )
-  }
-  return(ramclustr_obj)
+    return(ramclustr_obj)
 }