Mercurial > repos > iuc > virhunter
view virhunter.xml @ 1:9b12bc1b1e2c draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/VirHunter commit cea5a324cffd684e4cb08438fe5a305cfaf0f73a
author | iuc |
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date | Wed, 30 Nov 2022 17:31:52 +0000 |
parents | 457fd8fd681a |
children | ea2cccb9f73e |
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<tool id="virhunter" name="virhunter" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05"> <description> Deep learning method to identify viruses in sequencing datasets.. </description> <macros> <import>macros.xml</import> </macros> <xrefs> <xref type="bio.tools">virhunter</xref> </xrefs> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ mkdir -p '${predicted_fragments.extra_files_path}' && python '$__tool_directory__/predict.py' --test_ds '${fasta_file}' --weights '${weights.fields.path}' --out_path '${predicted_fragments.extra_files_path}' --return_viral True --limit $limit && cp '${predicted_fragments.extra_files_path}'/predicted_fragments.csv predicted_fragments.csv && cp '${predicted_fragments.extra_files_path}'/predicted.csv predicted.csv && cp '${predicted_fragments.extra_files_path}'/viral.fasta viral.fasta ]]></command> <inputs> <param name="fasta_file" type="data" format="fasta" label="DNA FASTA file(s)"/> <param name="weights" type="select" label="Select a reference model" help="If your model of interest is not listed, contact the Galaxy team"> <options from_data_table="virhunter_models"> <validator type="no_options" message="No models are available for the selected input dataset" /> </options> </param> <param argument="--limit" type="integer" min="0" value="750" label="Minimum contig length" help="Do not predict contigs shorter than this value. Default: 750" /> </inputs> <outputs> <data format="csv" name="predicted_fragments" from_work_dir="predicted_fragments.csv" label="${tool.name} on ${on_string}: predicted fragments"/> <data format="csv" name="predicted" from_work_dir="predicted.csv" label="${tool.name} on ${on_string}: predicted "/> <data format="fasta" name="viral" from_work_dir="viral.fasta" label="${tool.name} on ${on_string}: viral FASTA file" /> </outputs> <tests> <test> <param name="fasta_file" value="viruses.fasta"/> <param name="weights" value="test"/> <output name="predicted_fragments" file="predicted_fragments.csv" ftype="csv" lines_diff="2"/> <output name="predicted" file="predicted.csv" ftype="csv" lines_diff="2"/> <output name="viral" file="viral.fasta" ftype="fasta" lines_diff="2"/> </test> </tests> <help> <![CDATA[ VirHunter is a deep learning method that uses Convolutional Neural Networks (CNNs) and a Random Forest Classifier to identify viruses in sequening datasets. More precisely, VirHunter classifies previously assembled contigs as viral, host and bacterial (contamination). ]]></help> <expand macro="citations" /> </tool>