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1 <tool id="fathmm_web" name="FATHMM">
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2 <description>fathmm web service</description>
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3 <requirements>
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4 <requirement type="package" version="2.2.1">requests</requirement>
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5 <requirement type="python-module">requests</requirement>
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6 </requirements>
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7 <command interpreter="python">fathmm.py --input $input --output $output --threshold $threshold
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8 </command>
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9 <inputs>
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10 <param name="input" format="txt" type="data" label="Input variants" />
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11 <param name="threshold" type="float" label="Threshold cutoff" value="-0.75" help="Predictions with scores less than this indicate that the mutation is potentially associated with cancer" />
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12 </inputs>
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13 <outputs>
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14 <data name="output" format="tabular"/>
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15 </outputs>
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16 <tests>
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17 <test>
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18 <param name="input" value="fathmm_input.txt"/>
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19 <param name="threshold" value="-0.75" />
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20 <output name="output" file="fathmm_output.tab" lines_diff="2"/>
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21 </test>
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22 </tests>
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23 <help>
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24
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25
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26 **What it does**
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27
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28
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29 This script calls FATHMM(http://supfam3.cs.bris.ac.uk/FATHMM/about.html) Web API to fetch
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30 predict functional impact of mutations.
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31
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32 Input is a plain text file:
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33
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34 1. <protein> <substitution>
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35
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36 2. dbSNP rs identifiers
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37
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38
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39 Where <protein> is the protein identifier and
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40 <substitution> is the amino acid substitution in the conventional one letter format.
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41 Multiple substitutions can be entered on a single line and should be separated by a comma.
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42 SwissProt/TrEMBL, RefSeq and Ensembl protein identifiers are accepted:
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43
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44 P43026 L441P
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45 ENSP00000325527 N548I,E1073K,C2307S
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46
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47
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48
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49 **Citations**
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50
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51 If you use this tool in Galaxy, please cite :
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52
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53 Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GLA, Edwards KJ, Day INM, Gaunt, TR. (2013).
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54 Predicting the Functional, Molecular and PhenotypicConsequences of Amino Acid Substitutions using
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55 Hidden Markov Models. Hum. Mutat., 34:57-65
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56
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57 Shihab HA, Gough J, Cooper DN, Day INM, Gaunt, TR. (2013). Predicting the Functional Consequences
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58 of Cancer-Associated Amino Acid Substitutions. Bioinformatics 29:1504-1510.
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59
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60 Shihab HA, Gough J, Mort M, Cooper DN, Day INM, Gaunt, TR. (2014).
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61 Ranking Non-Synonymous Single Nucleotide Polymorphisms based on Disease Concepts. In Press
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62
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63 </help>
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64 </tool>
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65
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