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Merge pull request #2955 from bgruening/seqwish
add seqwish
2 parents 848c47f + 13e305d commit eff85ef

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tools/seqwish/.shed.yml

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categories:
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- Sequence Analysis
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- Variant Analysis
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homepage_url: https://github.com/ekg/seqwish
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description: Alignment to variation graph inducer
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long_description: |
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seqwish implements a lossless conversion from pairwise alignments between sequences to a variation graph encoding the sequences and their alignments.
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owner: iuc
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remote_repository_url: https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqwish/
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type: unrestricted

tools/seqwish/seqwish.xml

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<tool id="seqwish" name="seqwish" version="@TOOL_VERSION@" >
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<description>Alignment to variation graph inducer</description>
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<macros>
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<token name="@TOOL_VERSION@">0.4</token>
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</macros>
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<requirements>
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<requirement type="package" version="@TOOL_VERSION@">seqwish</requirement>
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</requirements>
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<command detect_errors="exit_code"><![CDATA[
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seqwish
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-p '$paf_alns'
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-s ${ ' '.join(["'%s'" % x for x in $seqs]) }
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--gfa='$out_gfa'
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#if $m:
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-m '$m'
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#end if
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--threads=\${GALAXY_SLOTS:-1}
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#if str($r):
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-r $r
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#end if
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#if str($k):
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-k $k
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#end if
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#if str($B):
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-B $B
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#end if
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]]></command>
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<inputs>
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<param argument="--paf-alns" type="data" format="paf" label="Induce the graph from these PAF formatted alignments" />
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<param argument="--seqs" type="data" format="fasta,fasta.gz,fastq,fastq.gz" multiple="true" label="The sequences used to generate the alignments" />
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<param argument="-m" type="data" optional="true" format="txt,tabular" label="Subset the input alignments"
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help="" />
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<param argument="-r" type="integer" min="1" optional="true" label="Limit copies of a given input base"
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help="Limit transitive closure to include no more than N copies of a given input base" />
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<param argument="-k" type="integer" min="1" optional="true" label="Filter exact matches below this length"
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help="This can smooth the graph locally and prevent the formation of complex local graph topologies from forming due to differential alignments." />
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<param argument="-B" type="integer" min="1" optional="true" label="Number of bp to use for transitive closure batch"
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help="" />
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</inputs>
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<outputs>
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<data name="out_gfa" format="gfa1" label="${tool.name} on ${on_string}" />
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</outputs>
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<tests>
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<test>
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<param name="seqs" value="A-3105.fa.gz" />
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<param name="paf_alns" value="A-3105.paf.gz" />
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<output name="out_gfa" md5="176f9b4be76a2e69550da9b9c39ac5eb" />
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</test>
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<test>
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<param name="seqs" value="A-3105.fa.gz" />
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<param name="paf_alns" value="A-3105.paf.gz" />
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<param name="r" value="3000" />
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<param name="k" value="1" />
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<param name="B" value="1000000" />
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<output name="out_gfa" md5="176f9b4be76a2e69550da9b9c39ac5eb" />
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</test>
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</tests>
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<help><![CDATA[
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These **seq**uences **wish** they were squished into a graph.
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seqwish implements a lossless conversion from pairwise alignments between sequences to a variation graph encoding the sequences
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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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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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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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large numbers of noisy input sequences. Memory usage during construction and traversal is limited by the use of sorted
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disk-backed arrays and succinct rank/select dictionaries to record a queryable version of the graph.
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]]></help>
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<citations>
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</citations>
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</tool>
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