Mercurial > repos > galaxyp > pyprophet_score

comparison pyprophet_score.xml @ 2:8b30c8ffa687 draft

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"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/pyprophet commit d1c34e31a93761cf7cfd4068bcdb70495d4d90bb"
author galaxyp
date Tue, 14 Apr 2020 10:53:02 -0400
parents 00816d9855fc
children
comparison
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1:00816d9855fc 2:8b30c8ffa687
1 <tool id="pyprophet_score" name="PyProphet score" version="@VERSION@.1"> 1 <tool id="pyprophet_score" name="PyProphet score" version="@VERSION@.2">
2 <description> 2 <description>
3 Error-rate estimation for MS1, MS2 and transition-level data 3 Error-rate estimation for MS1, MS2 and transition-level data
4 </description> 4 </description>
5 <macros> 5 <macros>
6 <import>macros.xml</import> 6 <import>macros.xml</import>
8 <expand macro="requirements"/> 8 <expand macro="requirements"/>
9 <command detect_errors="aggressive"> 9 <command detect_errors="aggressive">
10 <![CDATA[ 10 <![CDATA[
11 pyprophet score 11 pyprophet score
12 --in='$input' 12 --in='$input'
13 --classifier=$conditional_classifier.classifier
14
13 #if str($conditional_classifier.classifier)=='XGBoost': 15 #if str($conditional_classifier.classifier)=='XGBoost':
14 --classifier=$conditional_classifier.classifier
15 $conditional_classifier.xgb_autotune 16 $conditional_classifier.xgb_autotune
16 #elif str($conditional_classifier.classifier)=='LDA': 17 #end if
17 --classifier=$conditional_classifier.classifier 18 #if $apply_weights:
18 #elif str($conditional_classifier.classifier)=='prev_weights': 19 --apply_weights='$apply_weights'
19 --apply_weights=$conditional_classifier.apply_weights
20 #end if 20 #end if
21 --xeval_fraction=$xeval_fraction 21 --xeval_fraction=$xeval_fraction
22 --xeval_num_iter=$xeval_num_iter 22 --xeval_num_iter=$xeval_num_iter
23 --level=$level 23 --level=$level
24 --ss_initial_fdr=$ss_initial_fdr 24 --ss_initial_fdr=$ss_initial_fdr
48 ]]> 48 ]]>
49 </command> 49 </command>
50 <inputs> 50 <inputs>
51 <param name="input" type="data" format="osw" label="Input file" help="This file needs to be in OSW format (--in)" /> 51 <param name="input" type="data" format="osw" label="Input file" help="This file needs to be in OSW format (--in)" />
52 <conditional name="conditional_classifier"> 52 <conditional name="conditional_classifier">
53 <param name="classifier" type="select" label="Either a 'LDA' or 'XGBoost' classifier is used for semi-supervised learning or previously calculated Pyprophet score weights can be loaded" help="(--classifier)"> 53 <param argument="--classifier" type="select" label="Either a 'LDA' or 'XGBoost' classifier is used for semi-supervised learning" >
54 <option value="LDA" selected="True" >LDA</option> 54 <option value="LDA" selected="True" >LDA</option>
55 <option value="XGBoost">XGBoost</option> 55 <option value="XGBoost">XGBoost</option>
56 <option value="prev_weights">Apply previously calculated weights</option>
57 </param> 56 </param>
58 <when value="LDA"/> 57 <when value="LDA"/>
59 <when value="XGBoost"> 58 <when value="XGBoost">
60 <param name="xgb_autotune" type="boolean" truevalue="--xgb_autotune" falsevalue="--no-xgb_autotune" label="XGBoost: Autotune hyperparameters" help="(--xgb_autotune / --no-xgb_autotune)"/> 59 <param name="xgb_autotune" type="boolean" truevalue="--xgb_autotune" falsevalue="--no-xgb_autotune" label="XGBoost: Autotune hyperparameters" help="(--xgb_autotune / --no-xgb_autotune)"/>
61 </when> 60 </when>
62 <when value="prev_weights">
63 <param name="apply_weights" type="data" format="osw" label="Apply PyProphet score weights file instead of semi-supervised learning." help="(--apply_weights)" />
64 </when>
65 </conditional> 61 </conditional>
62 <param argument="apply_weights" type="data" format="osw" optional="True" label="Apply PyProphet score weights file (osw format) instead of semi-supervised learning." />
66 <param argument="--level" type="select" display="radio" label="The data level selected for scoring. 'ms1ms2' integrates both MS1- and MS2-level scores and can be used instead of 'ms2'-level results" > 63 <param argument="--level" type="select" display="radio" label="The data level selected for scoring. 'ms1ms2' integrates both MS1- and MS2-level scores and can be used instead of 'ms2'-level results" >
67 <option value="ms1" >MS1</option> 64 <option value="ms1" >MS1</option>
68 <option value="ms2" >MS2</option> 65 <option value="ms2" >MS2</option>
69 <option value="ms1ms2" selected="True" >MS1MS2</option> 66 <option value="ms1ms2" selected="True" >MS1MS2</option>
70 <option value="transition">transition</option> 67 <option value="transition">transition</option>
119 <output name="output" file="score.osw" compare="sim_size" /> 116 <output name="output" file="score.osw" compare="sim_size" />
120 <output name="score_report" file="score_report.pdf" compare="sim_size" /> 117 <output name="score_report" file="score_report.pdf" compare="sim_size" />
121 </test> 118 </test>
122 <test> 119 <test>
123 <param name="input" value="merged.osw" ftype="osw"/> 120 <param name="input" value="merged.osw" ftype="osw"/>
124 <conditional name="conditional_classifier"> 121 <param name="apply_weights" value="score.osw" ftype="osw"/>
125 <param name="classifier" value="prev_weights"/>
126 <param name="apply_weights" value="score.osw" ftype="osw"/>
127 </conditional>
128 <param name="level" value="ms2"/> 122 <param name="level" value="ms2"/>
129 <param name="xeval_num_iter" value="2" /> 123 <param name="xeval_num_iter" value="2" />
130 <param name="ss_num_iter" value="2" /> 124 <param name="ss_num_iter" value="2" />
131 <param name="pi0_lambda_start" value="0.1" /> 125 <param name="pi0_lambda_start" value="0.1" />
132 <param name="pi0_lambda_end" value="0.3" /> 126 <param name="pi0_lambda_end" value="0.3" />
150 144
151 ]]> 145 ]]>
152 </help> 146 </help>
153 <expand macro="citations"/> 147 <expand macro="citations"/>
154 </tool> 148 </tool>
149