view tools/myTools/1_sfa_exp.xml @ 1:7e5c71b2e71f draft default tip

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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>