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1 <tool id="oncodrivefm_tool" name="OncodriveFM">
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2 <description>OncodriveFM </description>
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1
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3 <requirements>
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4 <requirement type="package" version="2.0.1">requests</requirement>
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5 </requirements>
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6 <tool_dependency>
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7 <package name="oncodrivefm">
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8 <install version="0.6-dev">
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9 <actions>
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10 <action type="setup_virtualenv">distribute</action>
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11 <action type="setup_virtualenv">python-dateutil==2.1</action>
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12 <action type="setup_virtualenv">pytz==2013b</action>
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13 <action type="setup_virtualenv">numpy==1.7.1</action>
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14 <action type="setup_virtualenv">scipy==0.12.0</action>
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15 <action type="setup_virtualenv">pandas==0.12.0</action>
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16 <action type="setup_virtualenv">statsmodels==0.4.3</action>
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17 <action type="setup_virtualenv">https://bitbucket.org/bbglab/oncodrivefm/get/master.tar.gz</action>
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18 </actions>
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19 </install>
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20 <readme>OncodriveFm avalable at https://bitbucket.org/bbglab/oncodrivefm/</readme>
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21 </package>
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22 </tool_dependency>
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23
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24 <command interpreter="python">
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25 #if $mappingpathcondition.hasmapfile=="yes"
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26 oncodrivefm_tool.py -N $samplings -e $estimator --gt $gene_threshold --pt $pathway_threshold -s $slices -m $mapping_path -o1 $output1 -o2 $output2 -i $input
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27 #else
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28 oncodrivefm_tool.py -N $samplings -e $estimator --gt $gene_threshold --pt $pathway_threshold -s $slices -o1 $output1 -o2 $output2 -i $input
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29 #end if
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30 </command>
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31 <inputs>
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32 <param name="input" format="tabular" type="data" label="Input" />
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33 <param name="samplings" type="integer" label="Samplings" help="Number of samplings to compute the FM bias pvalue" optional="true" value="10000"/>
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34
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35 <param name="estimator" type="select" label="Estimator" help="Test estimator for computation" optional="true">
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36 <option value="median">Median</option>
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37 <option value="mean">Mean</option>
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38 </param>
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39
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40
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41 <param name="gene_threshold" type="integer" label="Gene Threshold" help="Minimum number of mutations per gene to compute the FM bias" optional="true" value="2"/>
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42 <param name="pathway_threshold" type="integer" label="Pathway Threshold" help="Minimum number of mutations per pathway to compute the FM bias" optional="true" value="10" />
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43 <param name="slices" type="text" label="Slices" help="Slices to process separated by commas(slices=SIFT,PPH2,MA)" optional="true" value="SIFT,PPH2,MA"/>
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44 <conditional name="mappingpathcondition">
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45 <param name="hasmapfile" type="select" label="Have a mapping gene file">
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46 <option value="no">No</option>
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47 <option value="yes">Yes</option>
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48 </param>
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49 <when value="yes">
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50 <param name="mapping_path" type="data" format="tabular" label=" File with mappings between genes and pathways to be analysed"/>
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51 </when>
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52 </conditional>
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53 </inputs>
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54 <outputs>
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55
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56 <data format="tabular" name="output1"/>
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57 <data format="tabular" name="output2" >
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58 <filter>mappingpathcondition["hasmapfile"]=="yes"</filter>
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59 </data>
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60 </outputs>
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61 <help>
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62 **What it does**
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63 Oncodrive-fm is an approach to uncover driver genes or gene modules.
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64 It computes a metric of functional impact using three well-known methods (SIFT, PolyPhen2 and MutationAssessor)
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65 and assesses how the functional impact of variants found in a gene across several tumor samples deviates from
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66 a null distribution. It is thus based on the assumption that any bias towards the accumulation of variants
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67 with high functional impact is an indication of positive selection and can thus be used to detect candidate
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68 driver genes or gene modules.
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69
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70 **Citation**
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71 If you use this Galaxy tool in work leading to a scientific publication please cite:
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72
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73 Gonzalez-Perez A and Lopez-Bigas N. 2012. Functional impact bias reveals cancer drivers. Nucleic Acids Res., 10.1093/nar/gks743.
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74
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75 </tool>
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76
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