# HG changeset patch
# User galaxyp
# Date 1582673304 18000
# Node ID 611120fd1717b759e06c5c3ad5e2c04bf93695fc

"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/pyprophet commit a83d231286a8df67483df46e76b4b3a2ef90b251"

diff -r 000000000000 -r 611120fd1717 macros.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml	Tue Feb 25 18:28:24 2020 -0500
@@ -0,0 +1,23 @@
+<macros>
+    <token name="@VERSION@">2.1.4</token>
+
+    <xml name="requirements">
+    <requirements>
+        <requirement type="package" version="2.1.4">pyprophet</requirement>
+        <yield/>
+    </requirements>
+    </xml>
+
+    <xml name="citations">
+    <citations>
+        <citation type="doi">10.1038/nmeth.4398</citation>
+        <citation type="doi">10.1038/nbt.3908</citation>
+        <citation type="doi">10.1093/bioinformatics/btu686</citation>
+        <citation type="doi">10.1038/nmeth.1584</citation>
+        <yield/>
+    </citations>
+    </xml>
+
+    <token name="@link@">http://openswath.org/en/latest/docs/pyprophet.html</token>
+
+</macros>
diff -r 000000000000 -r 611120fd1717 pyprophet_peptide.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyprophet_peptide.xml	Tue Feb 25 18:28:24 2020 -0500
@@ -0,0 +1,91 @@
+<tool id="pyprophet_peptide" name="PyProphet peptide" version="@VERSION@.0">
+    <description>
+    Peptide error-rate estimation
+    </description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <command detect_errors="aggressive">
+    <![CDATA[
+        pyprophet peptide
+            --in='$input'
+            --context=$context
+            $parametric
+            $pfdr
+        --pi0_lambda=$pi0_lambda_start $pi0_lambda_end $pi0_lambda_steps
+        --pi0_method=$pi0_method
+        --pi0_smooth_df=$pi0_smooth_df
+        $pi0_smooth_log
+        $lfdr_truncate
+        $lfdr_monotone
+        --lfdr_transformation=$lfdr_transformation
+        --lfdr_adj=$lfdr_adj
+        --lfdr_eps=$lfdr_eps
+        --out='./output.osw' && mv *_peptide.pdf peptide.pdf
+
+
+    ]]>
+    </command>
+    <inputs>
+        <param name="input" type="data" format="osw" label="Input file" help="This file needs to be in OSW format (--in)" />
+        <param argument="--context" type="select" display="radio" label="Context to estimate protein-level FDR control" >
+          <option value="run-specific" selected="True" >run-specific</option>
+          <option value="experiment-wide">experiment-wide</option>
+          <option value="global">global</option>
+        </param>
+<!-- sollte peptide-level FDR heißen?-->
+        <param name="parametric" type="boolean" truevalue="--parametric" falsevalue="--no-parametric" label="Do parametric estimation of p-values" help="(--parametric / --no-parametric)"/>
+        <param name="pfdr" type="boolean" truevalue="--pfdr" falsevalue="--no-pfdr" label="Compute positive false discovery rate (pFDR) instead of FDR" help="(--pfdr / --no-pfdr)"/>
+        <param name="pi0_lambda_start" type="float" value="0.1" label="Use non-parametric estimation of p-values. Start value" help="(--pi0_lambda)"/>
+        <param name="pi0_lambda_end" type="float" value="0.5" label="Use non-parametric estimation of p-values. End value" help="(--pi0_lambda)"/>
+        <param name="pi0_lambda_steps" type="float" value="0.05" label="Use non-parametric estimation of p-values. Steps value" help="(--pi0_lambda)"/>
+        <param argument="pi0_method" type="select" display="radio" label="Either 'smoother' or 'bootstrap'; the method for automatically choosing tuning parameter in the estimation of pi_0, the proportion of true null hypotheses" >
+          <option value="bootstrap" selected="True" >bootstrap</option>
+          <option value="smoother">smoother</option>
+        </param>
+        <param argument="--pi0_smooth_df" type="integer" value="3" label="Number of degrees-of-freedom to use when estimating pi_0 with a smoother" />
+        <param name="pi0_smooth_log" type="boolean" truevalue="--pi0_smooth_log_pi0" falsevalue="--no-pi0_smooth_log_pi0" label="If True and pi0_method = 'smoother', pi0 will be estimated by applying a smoother to a scatterplot of log(pi0) estimates against the tuning parameter lambda" help="(--pi0_smooth_log_pi0 / --no-pi0_smooth_log_pi0)"/>
+        <param name="lfdr_truncate" type="boolean" truevalue="--lfdr_truncate" falsevalue="--no-lfdr_truncate" checked="True" label="If True, local FDR values >1 are set to 1" help="(--lfdr_truncate / --no-lfdr_truncate)"/>
+        <param name="lfdr_monotone" type="boolean" truevalue="--lfdr_monotone" falsevalue="--no-lfdr_monotone" checked="True" label="If True, local FDR values are non-decreasing with increasing p-values" help="(--lfdr_monotone / --no-lfdr_monotone)"/>
+        <param argument="--lfdr_transformation" type="select" display="radio" label="Either a 'probit' or 'logit' transformation is applied to the p-values so that a local FDR estimate can be formed that does not involve edge effects of the [0,1] interval in which the p-values lie" >
+          <option value="probit" selected="True" >probit</option>
+          <option value="logit">logit</option>
+        </param>
+        <param argument="--lfdr_adj" type="float" value="1.5" label="Numeric value that is applied as a multiple of the smoothing bandwidth used in the density estimation" />
+        <param argument="--lfdr_eps" type="float" value="1e-08" label="Numeric value that is threshold for the tails of the empirical p-value distribution" />
+    </inputs>
+    <outputs>
+        <data name="peptide_plots" format="pdf" label="${tool.name} on ${on_string}: peptides.pdf" from_work_dir="peptide.pdf" />
+        <data name="output" format="osw" label="${tool.name} on ${on_string}: peptide.osw" from_work_dir="output.osw" />
+    </outputs>
+    <tests>
+        <test expect_num_outputs="2">
+            <param name="input" value="score.osw" ftype="osw" />
+            <param name="context" value="experiment-wide" />
+            <output name="output" file="peptide1.osw" compare="sim_size" />
+            <output name="peptide_plots" file="peptide1.pdf" compare="sim_size" />
+        </test>
+        <test expect_num_outputs="2">
+            <param name="input" value="peptide1.osw" ftype="osw" />
+            <param name="context" value="global" />
+            <output name="output" file="peptide2.osw" compare="sim_size" />
+            <output name="peptide_plots" file="peptide2.pdf" compare="sim_size" />
+        </test>
+    </tests>
+    <help>
+<![CDATA[
+**What it does**
+
+PyProphet: Semi-supervised learning and scoring of OpenSWATH results.
+
+Infer peptides and conduct error-rate estimation in different contexts.
+
+PyProphet is a Python re-implementation of the mProphet algorithm (Reiter 2010 Nature Methods) optimized for SWATH-MS data acquired by data-independent acquisition (DIA). The algorithm was originally published in (Telemann 2014 Bioinformatics) and has since been extended to support new data types and analysis modes (Rosenberger 2017, Nature biotechnology and Nature methods).
+
+For more information, visit @link@
+
+]]>
+    </help>
+    <expand macro="citations"/>
+</tool>
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diff -r 000000000000 -r 611120fd1717 test-data/output.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.tabular	Tue Feb 25 18:28:24 2020 -0500
@@ -0,0 +1,1 @@
+transition_group_id	decoy	run_id	filename	RT	assay_rt	delta_rt	iRT	assay_iRT	delta_iRT	Sequence	FullPeptideName	Charge	mz	Intensity	aggr_prec_Peak_Area	aggr_prec_Peak_Apex	leftWidth	rightWidth	peak_group_rank	d_score	m_score	id	aggr_Peak_Area	aggr_Peak_Apex	aggr_Fragment_Annotation	ProteinName	m_score_peptide_experiment_wide	m_score_peptide_global	m_score_protein_experiment_wide	m_score_protein_global
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diff -r 000000000000 -r 611120fd1717 test-data/study_design.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/study_design.tabular	Tue Feb 25 18:28:24 2020 -0500
@@ -0,0 +1,3 @@
+Filename	Condition	BioReplicate	Run
+./TN22.mzML	late	1	1
+./TN23.mzML	early	2	2
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