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annotate mmuphin.xml @ 1:23d58581f349 draft default tip

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planemo upload for repository https://github.com/biobakery/MMUPHin commit 85ea7462e2b824c35b9d444f6dfced71e990a412
author iuc
date Fri, 16 May 2025 12:56:52 +0000
parents 3938766e5135
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3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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1 <tool id="mmuphin" name="mmuphin" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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2 <description>Performing meta-analyses of microbiome studies</description>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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3 <macros>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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4 <import>macros.xml</import>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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5 </macros>
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6 <expand macro="xrefs"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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7 <expand macro="requirements"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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8 <command detect_errors="exit_code"><![CDATA[
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9 Rscript '$rscript' &&
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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10 mv 'adjust_batch_diagnostic.pdf' '$diagnostic_plot_output'
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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11 ]]></command>
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13 <configfiles>
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14 <configfile name="rscript"><![CDATA[
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3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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16 library(MMUPHin)
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18 ## input files
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19 print("Read input files")
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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20 data <- read.csv("$input_data", sep = "\t", row.names=1, check.names = FALSE)
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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21 meta_data <- read.csv("$input_metadata", sep = "\t", row.names=1, check.names = FALSE)
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23 # Define control list
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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24 controls <- list("$additional_options.zero_inflation",
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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25 "$additional_options.pseudo_count",
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26 "$additional_options.conv",
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27 "$additional_options.maxit",
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28 "$additional_options.verbose",
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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29 "$additional_options.diagnostic_plot")
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31 #Perform batch adjustment
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33 # Convert the batch column in the data frame to character or factor
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35 batch <- colnames(meta_data[$batch_input - 1]) # Adjust to fetch the column name
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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36 meta_data[[batch]] <- as.factor(meta_data[[batch]]) # Convert the column to factor
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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37 cat("Batch Name:", unique(meta_data[[batch]]), "\n") # Print unique batch names for confirmation
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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38 cat("Batch Name:", batch, "\n")
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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40 ## handle the optional command line input
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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41 #if $covariates_input:
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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42 covariates_val <- list($covariates_input)
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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43 #else:
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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44 covariates_val <- list() # Assign an empty list if input is NULL or does not exist
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45 #end if
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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47 covariates <- c()
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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49 # Process covariates only if they exist
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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50 if (length(covariates_val) > 0) {
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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51 for (i in covariates_val) {
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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52 covariates <- c(covariates, colnames(meta_data[i - 1]))
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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53 }
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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54 cat("Covariates Names:", covariates, "\n")
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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55 } else {
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56 cat("No covariates provided.\n")
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57 }
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59 result <- adjust_batch(feature_abd = data,
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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60 batch = batch,
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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61 covariates = covariates,
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62 data = meta_data,
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63 control=controls
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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64 )
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66 # Save results into output files
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67
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68 write.table(result\$feature_abd_adj, file="$output", quote = FALSE, sep="\t", col.names=NA)
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69
0
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70 ]]></configfile>
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71 </configfiles>
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72
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73 <inputs>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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74 <param name="input_data" type="data" format="tabular" label="Abundance (or features) file" help="TSV file where columns represent samples and rows include abundance values for features such as taxa, genes, or other biological entities across those samples."/>
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75 <param name="input_metadata" type="data" format="tabular" label="Metadata file" help="TSV file with sample metadata, where columns represent attributes and rows include attribute values for a sample"/>
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76 <param argument="batch_input" type="data_column" data_ref="input_metadata" use_header_names="true" label="Batch identifier column" help="Select the column in your metadata file that contains the batch identifier (e.g., studyID, batchID) used to group samples for batch correction."/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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77 <param argument="covariates_input" type="data_column" data_ref="input_metadata" use_header_names="true" multiple="true" optional="true" label="Covariates Column(s)" help="Select the column(s) in your metadata file that contain covariates (e.g., age, gender, or environmental factors) to be included in the batch correction process." />
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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78 <section name="additional_options" title="Additional Options" expanded="true">
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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79 <param argument="zero_inflation" type="boolean" truevalue="zero_inflation TRUE" falsevalue="zero_inflation FALSE" checked="true" label="Run zero-inflated model"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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80 <param argument="pseudo_count" type="float" optional="true" label="Pseudo_count" help="Pseudo count to add feature_abd before the methods' log transformation. Default to the half of the minimal non-zero values in feature_abd" />
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81 <param argument="conv" type="float" value="0.0001" min="0.000001" max="0.001" optional="true" label="Convergence threshold" help="Convergence threshold for the method's iterative algorithm for shrinking batch effect parameters."/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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82 <param argument="maxit" type="float" optional="true" value="1000" label="Maximum number of iterations" help="Maximum number of iterations allowed for the method's iterative algorithm. Default to 1000"/>
1
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83 <param argument="verbose" type="hidden" value="False" label="Print verbose information"/>
0
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84 <param argument="diagnostic_plot" type="boolean" truevalue="diagnostic_plot TRUE" falsevalue="diagnostic_plot FALSE" checked="true" label="Generate diagnostic figure file"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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85 </section>
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86 </inputs>
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87
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88 <outputs>
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89 <data name="output" format="tabular" label="Adjusted abundance table"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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90 <data name="diagnostic_plot_output" format="pdf" label="diagnostic figure file">
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91 <filter>
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92 additional_options['diagnostic_plot'] is True
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93 </filter>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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94 </data>
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95 </outputs>
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96
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97 <tests>
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98 <test expect_num_outputs="2">
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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99 <param name="input_data" value="CRC_abd.tsv"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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100 <param name="input_metadata" value="CRC_meta.tsv"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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101 <param name="batch_input" value="29"/>
3938766e5135 planemo upload for repository https://github.com/biobakery/MMUPHin commit 9d6123a18805224b03c0558647cd079624886361
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102 <param name="covariates_input" value="4"/>
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103 <section name="additional_options">
1
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104 <param name="zero_inflation" value="True"/>
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105 <param name="pseudo_count" value="3"/>
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106 <param name="conv" value="0.0001"/>
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107 <param name="maxit" value="1000"/>
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108 <param name="diagnostic_plot" value="True"/>
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109 </section>
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110 <output name="output" file="CRC_abd_corrected.tsv" ftype="tabular"/>
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111 <output name="diagnostic_plot_output" file="diagnostic.pdf" ftype="pdf"/>
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112 </test>
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113 <test expect_num_outputs="2">
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114 <param name="input_data" value="CRC_abd.tsv"/>
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115 <param name="input_metadata" value="CRC_meta.tsv"/>
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116 <param name="batch_input" value="7"/>
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117 <section name="additional_options">
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118 <param name="zero_inflation" value="True"/>
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119 <param name="pseudo_count" value="3"/>
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120 <param name="conv" value="0.0001"/>
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121 <param name="maxit" value="1000"/>
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122 <param name="diagnostic_plot" value="True"/>
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123 </section>
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124 <output name="output" file="CRC_abd_corrected2.tsv" ftype="tabular"/>
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125 <output name="diagnostic_plot_output" file="diagnostic2.pdf" ftype="pdf"/>
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126 </test>
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127 <test expect_num_outputs="2">
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128 <param name="input_data" value="CRC_abd.tsv"/>
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129 <param name="input_metadata" value="CRC_meta.tsv"/>
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130 <param name="batch_input" value="29"/>
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131 <param name="covariates_input" value="4,6"/>
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132 <section name="additional_options">
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133 <param name="zero_inflation" value="True"/>
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134 <param name="pseudo_count" value="3"/>
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135 <param name="conv" value="0.0001"/>
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136 <param name="maxit" value="1000"/>
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137 <param name="diagnostic_plot" value="True"/>
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138 </section>
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139 <output name="output" file="CRC_abd_corrected3.tsv" ftype="tabular"/>
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140 <output name="diagnostic_plot_output" file="diagnostic3.pdf" ftype="pdf"/>
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141 </test>
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142 </tests>
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143 <help><![CDATA[
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144 @HELP_HEADER@
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145 MmuPHin
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146 =========
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147 MMUPHin is an R package implementing meta-analysis methods for microbial community profiles. Meta-analysis methods are statistical techniques used to combine and synthesize data from multiple independent studies, typically to derive a more precise or generalizable conclusion. This approach is commonly used in fields such as medicine, psychology, and biology to aggregate research findings and increase the statistical power of analyses by pooling data from different experiments or studies. MMUPHin has interface for:
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148
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149 Performing batch effect adjustment :
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150 ------------------------------------------------------------------
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151 It aims to correct for technical batch effects in microbial feature abundances. Batch effects refer to variations in data that arise not from the biological or experimental variables of interest but due to differences in technical or procedural factors during data collection or processing. For example:
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152
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153 Different equipment or lab environments.
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154 Different operators handling the experiment.
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155 Variations in sample preparation, sequencing runs, or platforms.
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156
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157 These unwanted variations can obscure true biological signals and introduce bias, making it critical to adjust for batch effects to ensure accurate and comparable results across datasets.
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158
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159 Inputs for batch effect adjustment:
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160 ======================================
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161 A feature-by-sample abundance matrix (e.g., microbial abundances).
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162 A metadata file, which contains information about samples, including batch identifiers and optional covariates.
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163
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164 Output:
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165 =========
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166 A batch-adjusted abundance matrix for downstream analyses.
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167 A diagnostic plot output showing change before and after batch correction.
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168
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169 ]]></help>
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170 <expand macro="citations"/>
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171 </tool>