annotate seqwish.xml @ 0:7f7a074326ac draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqwish/ commit eff85ef0f4297e12deda88b534627b231e218bde"
author iuc
date Wed, 08 Apr 2020 11:23:40 -0400
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children 189ae8d7e08e
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7f7a074326ac "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqwish/ commit eff85ef0f4297e12deda88b534627b231e218bde"
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1 <tool id="seqwish" name="seqwish" version="@TOOL_VERSION@" >
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2 <description>Alignment to variation graph inducer</description>
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3 <macros>
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4 <token name="@TOOL_VERSION@">0.4</token>
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5 </macros>
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6 <requirements>
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7 <requirement type="package" version="@TOOL_VERSION@">seqwish</requirement>
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8 </requirements>
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9 <command detect_errors="exit_code"><![CDATA[
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10 seqwish
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11 -p '$paf_alns'
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12 -s ${ ' '.join(["'%s'" % x for x in $seqs]) }
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13 --gfa='$out_gfa'
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14 #if $m:
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15 -m '$m'
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16 #end if
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17 --threads=\${GALAXY_SLOTS:-1}
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18 #if str($r):
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19 -r $r
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20 #end if
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21 #if str($k):
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22 -k $k
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23 #end if
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24 #if str($B):
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25 -B $B
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26 #end if
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27 ]]></command>
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28 <inputs>
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29 <param argument="--paf-alns" type="data" format="paf" label="Induce the graph from these PAF formatted alignments" />
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30 <param argument="--seqs" type="data" format="fasta,fasta.gz,fastq,fastq.gz" multiple="true" label="The sequences used to generate the alignments" />
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31 <param argument="-m" type="data" optional="true" format="txt,tabular" label="Subset the input alignments"
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32 help="" />
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33 <param argument="-r" type="integer" min="1" optional="true" label="Limit copies of a given input base"
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34 help="Limit transitive closure to include no more than N copies of a given input base" />
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35 <param argument="-k" type="integer" min="1" optional="true" label="Filter exact matches below this length"
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36 help="This can smooth the graph locally and prevent the formation of complex local graph topologies from forming due to differential alignments." />
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37 <param argument="-B" type="integer" min="1" optional="true" label="Number of bp to use for transitive closure batch"
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38 help="" />
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39 </inputs>
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40
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41 <outputs>
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42 <data name="out_gfa" format="gfa1" label="${tool.name} on ${on_string}" />
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43 </outputs>
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44
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45 <tests>
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46 <test>
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47 <param name="seqs" value="A-3105.fa.gz" />
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48 <param name="paf_alns" value="A-3105.paf.gz" />
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49 <output name="out_gfa" md5="176f9b4be76a2e69550da9b9c39ac5eb" />
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50 </test>
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51 <test>
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52 <param name="seqs" value="A-3105.fa.gz" />
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53 <param name="paf_alns" value="A-3105.paf.gz" />
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54 <param name="r" value="3000" />
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55 <param name="k" value="1" />
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56 <param name="B" value="1000000" />
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57 <output name="out_gfa" md5="176f9b4be76a2e69550da9b9c39ac5eb" />
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58 </test>
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59 </tests>
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60 <help><![CDATA[
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61 These **seq**uences **wish** they were squished into a graph.
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62
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63 seqwish implements a lossless conversion from pairwise alignments between sequences to a variation graph encoding the sequences
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64 and their alignments. As input we typically take all-versus-all alignments, but the exact structure of the alignment set may
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65 be defined in an application specific way. This algorithm uses a series of disk-backed sorts and passes over the alignment
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66 and sequence inputs to allow the graph to be constructed from very large inputs that are commonly encountered when working with
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67 large numbers of noisy input sequences. Memory usage during construction and traversal is limited by the use of sorted
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68 disk-backed arrays and succinct rank/select dictionaries to record a queryable version of the graph.
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69 ]]></help>
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70 <citations>
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71 </citations>
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72 </tool>