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feat(tools): icfree, add calibrator wrapper
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@guillaume-gricourt
guillaume-gricourt committed Nov 14, 2024
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123 changes: 123 additions & 0 deletions tools/icfree/calibrator.xml
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<tool id="icfree_calibrator" name="iCFree calibrator" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" license="MIT">
<description>Calculate yield based on fluorescence data and optionally apply calibration</description>
<macros>
<import>macros.xml</import>
</macros>
<expand macro="requirements"/>
<command detect_errors="exit_code"><![CDATA[
cp '$initial_data_file' 'initial_data.csv' &&
cp '$sampling_file' 'sampling.csv' &&
#if $adv.ref_file
cp '$adv.ref_file' 'reference.csv' &&
#end if
python -m icfree.learner.extractor
--initial_data_file 'initial_data.csv'
--sampling_file 'sampling.csv'
--output_file 'extractor.csv'
#if str($adv.num_samples) != ''
--num_samples '$adv.num_samples'
#end if
#if str($adv.num_replicates) != ''
--num_replicates '$adv.num_replicates'
#end if
&&
python -m icfree.learner.calibrator
--file 'extractor.csv'
--output 'calibrated.csv'
--jove_plus '$jove_plus'
--jove_minus '$jove_minus'
--r2_limit '$adv.r2_limit'
#if str($adv.num_control_points) != ''
--num_control_points '$adv.num_control_points'
#end if
#if $adv.ref_file
--ref_file 'reference.csv'
--plot '$output_graph'
#end if
#if str($adv.num_samples) != ''
--num '$adv.num_samples'
#end if
&&
mv 'calibrated.csv' '$output_calibrated' &&
mv 'calibrated_control_points.csv' '$output_control_points'
]]></command>
<inputs>
<param name="initial_data_file" type="data" format="csv" label="Initial file" help="Initial file"/>
<param name="sampling_file" type="data" format="csv" label="Sampling file" help="Sampling file"/>
<param argument="jove_plus" type="integer" label="Line number for Jove+ (1-based index)" help="Line number for Jove+ (1-based index)" />
<param argument="jove_minus" type="integer" label="Line number for Jove- (1-based index)" help="Line number for Jove- (1-based index)" />
<section name="adv" title="Advanced Options" expanded="false">
<param argument="num_samples" type="integer" optional="true" label="Number of samples" help="Number of samples" />
<!-- Extractor -->
<param argument="num_replicates" type="integer" optional="true" label="Number of replicates" help="Number of replicates." />
<!-- Calibrator -->
<param argument="r2_limit" type="float" value="0.8" label="R-squared limit for the regression" help="R-squared limit for the regression" />
<param argument="num_control_points" type="integer" optional="true" label="Number of control points to select" help="Number of control points to select" />
<param name="ref_file" type="data" optional="true" format="csv" label="Reference input file" help="Reference input file"/>
</section>
</inputs>
<outputs>
<data name="output_calibrated" format="csv" label="${tool.name} - Calibrated yields" />
<data name="output_control_points" format="csv" label="${tool.name} - Control points" />
<data name="output_graph" format="png" label="${tool.name} - Graph">
<filter>adv['ref_file']</filter>
</data>
</outputs>
<tests>
<test expect_num_outputs="2">
<!-- python -m icfree.learner.extractor -initial_data_file calibrator.input.initial_data.csv -sampling_file calibrator.input.sampling.csv -output_file calibrator.extractor_output.1.csv -->
<!-- python -m icfree.learner.calibrator -file calibrator.extractor_output.1.csv -output calibrator.output.csv -jove_plus 3 -jove_minus 2 -->
<param name="initial_data_file" value="calibrator.input.initial_data.csv" />
<param name="sampling_file" value="calibrator.input.sampling.csv" />
<param name="jove_plus" value="3" />
<param name="jove_minus" value="2" />
<output name="output_calibrated" ftype="csv">
<assert_contents>
<has_n_lines n="343" />
</assert_contents>
</output>
<output name="output_control_points" ftype="csv">
<assert_contents>
<has_n_lines n="11" />
</assert_contents>
</output>
</test>
<test expect_num_outputs="3">
<!-- python -m icfree.learner.extractor -initial_data_file calibrator.input.initial_data.csv -sampling_file calibrator.input.sampling.tsv -output_file calibrator.output.extractor.2.csv -num_samples 20 -num_replicates 3 -->
<!-- python -m icfree.learner.calibrator -file calibrator.output.extractor.2.csv -output calibrator.output.2.csv -jove_plus 4 -jove_minus 3 -r2_limit 0.9 -num 20 -num_control_points 4 -ref_file calibrator.input.ref.csv -->
<param name="initial_data_file" value="calibrator.input.initial_data.csv" />
<param name="sampling_file" value="calibrator.input.sampling.csv" />
<param name="ref_file" value="calibrator.input.ref.csv" />
<param name="num_samples" value="20" />
<param name="num_replicates" value="3" />
<param name="r2_limit" value="0.9" />
<param name="num_control_points" value="4" />
<param name="jove_plus" value="4" />
<param name="jove_minus" value="3" />
<output name="output_calibrated" ftype="csv">
<assert_contents>
<has_n_lines n="21" />
</assert_contents>
</output>
<output name="output_control_points" ftype="csv">
<assert_contents>
<has_n_lines n="21" />
</assert_contents>
</output>
<output name="calibrator_graph" ftype="png" >
<assert_contents>
<has_size value="45000" delta="1000" />
</assert_contents>
</output>
</test>

</tests>
<help><![CDATA[
Calibrator
==========
Calculate yield based on fluorescence data and apply calibration.
]]></help>
<expand macro="creator"/>
<expand macro="citation"/>
</tool>
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