Mercurial > repos > iuc > decontaminator
comparison decontaminator.xml @ 0:b856d3d95413 draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/decontaminator commit 3f8e87001f3dfe7d005d0765aeaa930225c93b72
| author | iuc |
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| date | Mon, 09 Jan 2023 13:27:09 +0000 |
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| -1:000000000000 | 0:b856d3d95413 |
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| 1 <tool id="decontaminator" name="decontaminator" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05"> | |
| 2 <description>Decontaminator is a deep learning helping tool that filters out phage or fungi contigs from plant virome RNAseq assemblies</description> | |
| 3 <macros> | |
| 4 <import>macros.xml</import> | |
| 5 </macros> | |
| 6 <xrefs> | |
| 7 <xref type="bio.tools">decontaminator</xref> | |
| 8 </xrefs> | |
| 9 <expand macro="requirements"/> | |
| 10 <command detect_errors="exit_code"><![CDATA[ | |
| 11 mkdir -p '${predicted_fragments.extra_files_path}' && | |
| 12 python '$__tool_directory__/predict.py' | |
| 13 --test_ds '${fasta_file}' | |
| 14 --weights '${weights.fields.path}' | |
| 15 --out_path '${predicted_fragments.extra_files_path}' | |
| 16 --return_viral True | |
| 17 && cp '${predicted_fragments.extra_files_path}'/predicted_fragments.tsv predicted_fragments.tsv | |
| 18 && cp '${predicted_fragments.extra_files_path}'/predicted.tsv predicted.tsv | |
| 19 && cp '${predicted_fragments.extra_files_path}'/viral.fasta viral.fasta | |
| 20 | |
| 21 ]]></command> | |
| 22 <inputs> | |
| 23 <param name="fasta_file" type="data" format="fasta" label="DNA FASTA file"/> | |
| 24 <param name="weights" type="select" label="Select a reference model" help="If your model of interest is not listed, contact the Galaxy team"> | |
| 25 <options from_data_table="decontaminator_models"> | |
| 26 <validator type="no_options" message="No models are available for the selected input dataset" /> | |
| 27 </options> | |
| 28 </param> | |
| 29 </inputs> | |
| 30 <outputs> | |
| 31 <data format="tabular" name="predicted_fragments" from_work_dir="predicted_fragments.tsv" label="${tool.name} on ${on_string}: predicted fragments"/> | |
| 32 <data format="tabular" name="predicted" from_work_dir="predicted.tsv" label="${tool.name} on ${on_string}: predicted "/> | |
| 33 <data format="fasta" name="viral" from_work_dir="viral.fasta" label="${tool.name} on ${on_string}: viral FASTA file" /> | |
| 34 </outputs> | |
| 35 <tests> | |
| 36 <test> | |
| 37 <param name="fasta_file" value="viruses.fasta"/> | |
| 38 <param name="weights" value="test"/> | |
| 39 <output name="predicted_fragments" file="predicted_fragments.tsv" ftype="tabular" lines_diff="2"/> | |
| 40 <output name="predicted" file="predicted.tsv" ftype="tabular" lines_diff="2"/> | |
| 41 <output name="viral" file="viral.fasta" ftype="fasta" lines_diff="2"/> | |
| 42 </test> | |
| 43 </tests> | |
| 44 <help> | |
| 45 <![CDATA[ | |
| 46 Decontaminator is a deep learning method that uses Convolutional Neural Networks (CNNs) and a Random Forest Classifier to identify viruses in | |
| 47 sequening datasets. More precisely, VirHunter classifies previously assembled contigs as viral, host and bacterial (contamination). | |
| 48 ]]></help> | |
| 49 </tool> |