Mercurial > repos > iuc > hyphy_fubar

annotate hyphy_fubar.xml @ 3:d92fc00e1e9d draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/hyphy/ commit f14f2bae2b27dc04e574803c7d4442a64cfe43e4"
author iuc
date Fri, 14 Feb 2020 21:38:37 +0000
parents 0e02271cfc93
children 5807a4aef9e9
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1 <?xml version="1.0"?>
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2 <tool id="hyphy_fubar" name="HyPhy-FUBAR" version="@VERSION@+galaxy1">
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3 <description>Fast Unconstrained Bayesian AppRoximation</description>
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4 <macros>
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5 <import>macros.xml</import>
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6 </macros>
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7 <expand macro="requirements"/>
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8 <command detect_errors="exit_code"><![CDATA[
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9 ln -s '$input_file' fubar_input.fa &&
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10 ln -s '$input_nhx' fubar_input.nhx &&
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11 hyphy fubar
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12 --alignment ./fubar_input.fa
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13 --tree ./fubar_input.nhx
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14 --code '$gencodeid'
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15 --method '$posterior'
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16 --grid '$grid_points'
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17 --chains '$mcmc'
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18 --chain-length '$chain_length'
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19 --burn-in '$samples'
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20 --samples '$samples_per_chain'
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21 --concentration_parameter '$concentration'
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22 > '$fubar_log'
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23 ]]></command>
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24 <inputs>
1
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25 <expand macro="inputs"/>
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26 <expand macro="gencode"/>
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27 <param name="grid_points" type="integer" value="20" min="5" max="50" label="Grid points"/>
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28 <param name="posterior" type="select" label="Posterior estimation method">
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29 <option value="Metropolis-Hastings">Full Metropolis-Hastings MCMC algorithm</option>
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30 <option value="Collapsed-Gibbs">Collapsed Gibbs sampler</option>
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31 <option value="Variational-Bayes">0-th order Variational Bayes approximations</option>
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32 </param>
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33 <param name="mcmc" type="integer" value="5" min="2" max="20" label="Number of MCMC chains"/>
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34 <param name="chain_length" type="integer" value="2000000" min="500000" max="50000000" label="Length of each chain"/>
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35 <param name="samples" type="integer" value="1000000" min="100000" max="1900000" label="Samples to use for burn-in"/>
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36 <param name="samples_per_chain" type="integer" value="100" min="50" max="1000000" label="Samples to draw from each chain"/>
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37 <param name="concentration" type="float" value="0.5" min="0.001" max="1" label="Concentration parameter of the Dirichlet prior"/>
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38 </inputs>
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39 <outputs>
1
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40 <data name="fubar_log" format="txt"/>
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41 <data name="fubar_output" format="hyphy_results.json" from_work_dir="fubar_input.fa.FUBAR.json" />
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42 </outputs>
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43 <tests>
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44 <test>
1
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45 <param name="input_file" ftype="fasta" value="fubar-in1.fa"/>
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46 <param name="input_nhx" ftype="nhx" value="fubar-in1.nhx"/>
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47 <param name="posterior" value="Variational-Bayes"/>
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48 <output name="fubar_output" file="fubar-out1.json" compare="sim_size"/>
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49 </test>
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50 </tests>
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51 <help><![CDATA[
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52 Model-based selection analyses (such as those performed by PAML and HyPhy) can be slow, becoming impractical for large alignments. We present a method to model and detect selection much faster than existing methods and to leverage Bayesian MCMC to robustly account for parameter estimation errors.
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0943d89b7a25 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/hyphy/ commit 538d41e9789e18c8edb3dc68a1aabbee9b9f8bea
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54 Results: By exploiting some commonly used approximations, FUBAR can perform detection of positive selection under a model that allows rich site- to-site rate variation about 30 to 50 times faster than existing random effects likelihood methods, and 10 to 30 times faster than existing fixed effects likelihood methods. We introduce an ultra-fast MCMC routine that allows a flexible prior specification, with no parametric constraints on the prior shape. Furthermore, our method allows us to visualize Bayesian inference for each site, revealing the model supported by the data.
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56 See the online documentation_ for more information.
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58 .. _documentation: http://hyphy.org/methods/selection-methods/#fubar
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59 ]]></help>
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60 <expand macro="citations">
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61 <citation type="doi">10.1093/molbev/mst030</citation>
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62 </expand>
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63 </tool>