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comparison virhunter.xml @ 0:6052fcc0d113 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/VirHunter commit 628688c1302dbf972e48806d2a5bafe27847bdcc
author iuc
date Wed, 09 Nov 2022 12:18:36 +0000
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1 <tool id="virhunter" name="virhunter" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
2 <description>
3 Deep learning method to identify viruses in sequencing datasets..
4 </description>
5 <macros>
6 <import>macros.xml</import>
7 </macros>
8 <xrefs>
9 <xref type="bio.tools">virhunter</xref>
10 </xrefs>
11 <expand macro="requirements"/>
12 <command detect_errors="exit_code"><![CDATA[
13
14 mkdir -p '${predicted_fragments.extra_files_path}' &&
15 python '$__tool_directory__/predict.py'
16 --test_ds '${fasta_file}'
17 --weights '${weights.fields.path}'
18 --out_path '${predicted_fragments.extra_files_path}'
19 --return_viral True
20 --limit $limit
21 && cp '${predicted_fragments.extra_files_path}'/predicted_fragments.csv predicted_fragments.csv
22 && cp '${predicted_fragments.extra_files_path}'/predicted.csv predicted.csv
23 && cp '${predicted_fragments.extra_files_path}'/viral.fasta viral.fasta
24
25 ]]></command>
26 <inputs>
27 <param name="fasta_file" type="data" format="fasta" label="DNA FASTA file(s)"/>
28 <param name="weights" type="select" label="Select a reference model" help="If your model of interest is not listed, contact the Galaxy team">
29 <options from_data_table="virhunter_models">
30 <validator type="no_options" message="No models are available for the selected input dataset" />
31 </options>
32 </param>
33 <param argument="--limit" type="integer" min="0" value="750" label="Minimum contig length" help="Do not predict contigs shorter than this value. Default: 750" />
34 </inputs>
35 <outputs>
36 <data format="csv" name="predicted_fragments" from_work_dir="predicted_fragments.csv" label="${tool.name} on ${on_string}: predicted fragments"/>
37 <data format="csv" name="predicted" from_work_dir="predicted.csv" label="${tool.name} on ${on_string}: predicted "/>
38 <data format="fasta" name="viral" from_work_dir="viral.fasta" label="${tool.name} on ${on_string}: viral FASTA file" />
39 </outputs>
40 <tests>
41 <test>
42 <param name="fasta_file" value="viruses.fasta"/>
43 <param name="weights" value="test"/>
44 <output name="predicted_fragments" file="predicted_fragments.csv" ftype="csv" lines_diff="2"/>
45 <output name="predicted" file="predicted.csv" ftype="csv" lines_diff="2"/>
46 <output name="viral" file="viral.fasta" ftype="fasta" lines_diff="2"/>
47 </test>
48 </tests>
49
50 <help>
51 <![CDATA[
52 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).
53 ]]></help>
54 <expand macro="citations" />
55 </tool>