Mercurial > repos > laurenmarazzi > netisce_test
view tools/myTools/1_sfa_exp.xml @ 1:7e5c71b2e71f draft default tip
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author | laurenmarazzi |
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date | Wed, 22 Dec 2021 16:00:34 +0000 |
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<tool id="netisce1" name="Netisce Step 1" version="0.1.0" python_template_version="3.5"> <description>Estimates attractors from experimental data using Signal Flow Analysis.</description> <requirements> <requirement type="package" version="3.5.0">os</requirement> <requirement type="package" version="1.19.5">numpy</requirement> <requirement type="package" version="1.1.5">pandas</requirement> <requirement type="package" version="1.11.0">networkx</requirement> <requirement type="package" version="3.5.0">random</requirement> <requirement type="package" version="3.1.14">sfa</requirement> <requirement type="package" version="3.5.0">csv</requirement> <requirement type="package" version="3.5.0">sys</requirement> </requirements> <command>python3 '$__tool_directory__/bin/SFA_exp_attr.py' '$network' '$expression_data' exp_attrs.csv</command> <inputs> <param name="network" type="data" format="sif" label="Network"/> <param name="expression_data" type="data" format="csv" label="Expression Data"/> </inputs> <outputs> <data name="output" format="tabular" from_work_dir="attrs_exp.tsv" label="Experimental Attractors"/> </outputs> <tests> <test expect_num_outputs="1"> <param name="network" value="network.sif" /> <param name="expression_data" value="expressions.csv" /> <output name="output" file="attrs_exp.tsv" ftype="tsv" /> </test> </tests> <help> This tool estimates attractors for each experimental sample from normalized expression data using Signal Flow Analysis. Required Inputs: 1. network in sif format (activating edges as "activates", inhibitory edges as "inhibits") 2. normalized expression values for data sample </help> <citations> <citation type="doi">10.1038/s41598-019-50790-0</citation> </citations> </tool>