Mercurial > repos > iuc > concoct
view concoct.xml @ 7:eae7ee167917 draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/concoct commit 86e1afebec29c10ef1e31196b23c24fde2d086da
author | iuc |
---|---|
date | Sun, 12 Nov 2023 14:30:52 +0000 |
parents | 16672a3c9b65 |
children |
line wrap: on
line source
<tool id="concoct" name="CONCOCT" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> <description>for metagenome binning</description> <macros> <import>macros.xml</import> </macros> <expand macro="biotools"/> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ ## CONCOCT doesn't handle gzipped files. #if $composition_file.ext.endswith(".gz") gunzip -c '$composition_file' > 'composition_file.fa' && #else: ln -s '$composition_file' 'composition_file.fa' && #end if mkdir outdir && concoct --coverage_file '$coverage_file' --composition_file 'composition_file.fa' --clusters $advanced.clusters --kmer_length $advanced.kmer_length --threads \${GALAXY_SLOTS:-4} --length_threshold $advanced.length_threshold --read_length $advanced.read_length --total_percentage_pca $advanced.total_percentage_pca --basename 'outdir/' --seed $advanced.seed --iterations $advanced.iterations $advanced.no_cov_normalization $output.no_total_coverage --no_original_data $output.converge_out ]]></command> <inputs> <param argument="--coverage_file" type="data" format="tabular" label="Coverage file" help="Table where each row correspond to a contig, and each column correspond to a sample. The values are the average coverage for this contig in that sample"/> <param argument="--composition_file" type="data" format="fasta,fasta.gz" label="Composition file with sequences" help="It is named the composition file since it is used to calculate the kmer composition (the genomic signature) of each contig."/> <section name="advanced" title="Advanced options"> <param argument="--clusters" type="integer" min="0" value="400" label="Maximum number of clusters for the Variational Gaussian Mixture Model (VGMM) algorithm"/> <param argument="--kmer_length" type="integer" min="0" value="4" label="Kmer length"/> <param argument="--length_threshold" type="integer" min="0" value="1000" label="Sequence length threshold" help="Contigs shorter than this value will not be included"/> <param argument="--read_length" type="integer" min="0" value="100" label="Read length for coverage"/> <param argument="--total_percentage_pca" type="integer" min="0" value="90" label="Percentage of variance explained by the principal components for the combined data"/> <param argument="--seed" type="integer" min="0" value="1" label="Seed for clustering" help="Zero value will use random seed"/> <param argument="--iterations" type="integer" min="0" value="500" label="Maximum number of iterations for the Variational Bayes Gaussian Mixture Models (VBGMM)"/> <param argument="--no_cov_normalization" type="boolean" truevalue="--no_cov_normalization" falsevalue="" checked="false" label="Skip normalization and only do log transorm of the coverage?" help="By default, the coverage is normalized for samples, then normalized for contigs and finally log transformed. By setting this flag you skip the normalization and only do log transorm of the coverage."/> </section> <section name="output" title="Output"> <param argument="--no_total_coverage" type="boolean" truevalue="--no_total_coverage" falsevalue="" checked="false" label="Eliminate the total coverage column from the coverage data matrix?" help="By default, total coverage is included, independently of coverage normalization but previous to log transformation. Use this tag to escape this behaviour."/> <param argument="--converge_out" type="boolean" truevalue="--converge_out" falsevalue="" checked="false" label="Write convergence information to files?"/> <param name="log" type="boolean" checked="false" label="Output process log file?"/> </section> </inputs> <outputs> <data name="output_clustering" format="csv" from_work_dir="outdir/clustering_gt*" label="${tool.name} on ${on_string}: Clusters"/> <data name="process_log" format="txt" from_work_dir="outdir/log.txt" label="${tool.name} on ${on_string}: Log"> <filter>output['log']</filter> </data> <data name="output_pca_components" format="csv" from_work_dir="outdir/PCA_components_data_gt*" label="${tool.name} on ${on_string}: PCA components"/> <data name="output_pca_transformed" format="csv" from_work_dir="outdir/PCA_transformed_data_gt*" label="${tool.name} on ${on_string}: PCA transformed clusters"/> </outputs> <tests> <test expect_num_outputs="4"> <param name="coverage_file" value="coverage" ftype="tabular"/> <param name="composition_file" value="composition.fa" ftype="fasta"/> <section name="advanced"> <param name="clusters" value="400"/> <param name="kmer_length" value="4"/> <param name="length_threshold" value="1000"/> <param name="read_length" value="100"/> <param name="total_percentage_pca" value="100"/> <param name="seed" value="1"/> <param name="iterations" value="500"/> <param name="no_cov_normalization" value=""/> </section> <section name="output"> <param name="no_total_coverage" value=""/> <param name="converge_out" value=""/> <param name="log" value="true"/> </section> <output name="process_log" ftype="txt" compare="contains"> <assert_contents> <has_size value="786" delta="4"/> <has_text text="CONCOCT Finished"/> </assert_contents> </output> <output name="output_pca_components" ftype="csv"> <assert_contents> <has_size value="362924" delta="10"/> <has_text text="-5.90697200e-02"/> </assert_contents> </output> <output name="output_pca_transformed" ftype="csv"> <assert_contents> <has_size value="834200" delta="50"/> <has_text text="contig-21000001"/> </assert_contents> </output> <output name="output_clustering" ftype="csv"> <assert_contents> <has_size value="6923" delta="10"/> <has_text text="contig-21000001,"/> </assert_contents> </output> </test> <test expect_num_outputs="3"> <param name="coverage_file" value="coverage" ftype="tabular"/> <param name="composition_file" value="composition.fa.gz" ftype="fasta.gz"/> <section name="advanced"> <param name="clusters" value="400"/> <param name="kmer_length" value="4"/> <param name="length_threshold" value="1000"/> <param name="read_length" value="100"/> <param name="total_percentage_pca" value="100"/> <param name="seed" value="1"/> <param name="iterations" value="500"/> <param name="no_cov_normalization" value=""/> </section> <section name="output"> <param name="no_total_coverage" value=""/> <param name="converge_out" value=""/> <param name="log" value="false"/> </section> <output name="output_pca_components" ftype="csv"> <assert_contents> <has_size value="362924" delta="10"/> <has_text text="-5.90697200e-02"/> </assert_contents> </output> <output name="output_pca_transformed" ftype="csv"> <assert_contents> <has_size value="834200" delta="50"/> <has_text text="contig-21000001"/> </assert_contents> </output> <output name="output_clustering" ftype="csv"> <assert_contents> <has_size value="6923" delta="10"/> <has_text text="contig-21000001,"/> </assert_contents> </output> </test> </tests> <help><![CDATA[ **What it does** CONCOCT (Clustering cONtigs with COverage and ComposiTion) performs unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage data for multiple samples. CONCOCT can accurately (up to species level) bin metagenomic contigs. The tool accepts 2 inputs; a tabular file where each row corresponds to a contig and each column corresponds to a sample (the values are the average coverage for this contig in that sample) and a file containing sequences in fasta format. Three outputs are produced; clustering of the > 1000 kmer count, the PCA transformed matrix and the PCA components. @HELP_OVERVIEW@ ]]></help> <expand macro="citations"/> </tool>