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initial commit of pepnet #726

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11 changes: 11 additions & 0 deletions tools/pepnet/.shed.yml
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categories:
- Proteomics
description: De novo sequencing of tandem mass spectra
long_description: |
The state of the art Deep CNN neural network for de novo sequencing of tandem
mass spectra, currently works on unmodified HCD spectra of charges 1+ to 4+.
owner: galaxyp
name: pepnet
homepage_url: https://github.com/lkytal/PepNet
remote_repository_url: https://github.com/galaxyproteomics/tools-galaxyp/tools/pepnet
type: unrestricted
46 changes: 46 additions & 0 deletions tools/pepnet/pepnet.xml
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<tool id="pepnet" name="pepnet" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
<description>de novo sequencing of tandem mass spectra</description>
<macros>
<token name="@TOOL_VERSION@">1.0</token>
<token name="@VERSION_SUFFIX@">0</token>
</macros>
<requirements>
<requirement type="package" version="@TOOL_VERSION@">pepnet</requirement>
</requirements>
<command detect_errors="aggressive"><![CDATA[
denovo.py
--input '$input'
--model '$model'
--output '$output'
--default_charge '$default_charge'
]]></command>
<inputs>
<param argument="--input" type="data" multiple="false" format="mgf" label="Spectrum file"/>
<!--TODO add data table-->
<param argument="--model" type="data" multiple="false" format="hdf5" label="Peptide file" help="Model" />
<param argument="--default_charge" type="integer" value="-1" min="-1" label="Default charge" help="for spectra without charges, -1 means disabled"/>
</inputs>
<outputs>
<data name="output" format="tabular"/>
</outputs>
<tests>
<test expect_num_outputs="1">
<param name="input" location="https://zenodo.org/record/7869847/files/example.mgf?download=1"/>
<param name="model" location="https://zenodo.org/record/7869847/files/model.h5?download=1"/>
<output name="output" ftype="tabular">
<assert_contents>
<has_n_lines n="1"/>
<has_n_columns n="1"/>
</assert_contents>
</output>
</test>
</tests>
<help><![CDATA[
]]></help>
<citations>
<citation type="doi">10.1186/s40168-022-01454-1</citation>
<citation type="doi">10.1073/pnas.1722325115</citation>
<citation type="doi">10.1101/2021.03.29.437612</citation>
<citation type="doi">10.1093/bioinformatics/bty046</citation>
</citations>
</tool>
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