view NSPDK_sparseVect.xml @ 2:ee828c452161 draft

planemo upload for repository https://github.com/eteriSokhoyan/galaxytools/tree/branchForIterations/tools/GraphClust/NSPDK commit 057c2fd398055dc86eb2c00d8a74f301d5c231d9-dirty
author rnateam
date Wed, 22 Feb 2017 16:53:08 -0500
parents 90a4a2e7d876
children d10410cfd17a
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<tool id="nspdk_sparse" name="NSPDK_sparseVect" version="9.2">
	<requirements>
			<requirement type="package" version="0.1.8">graphclust-wrappers</requirement>
			<requirement type="package" version="9.2">nspdk</requirement>
	</requirements>
	<stdio>
		<exit_code range="1:" />
	</stdio>
	<command>
		<![CDATA[


      'NSPDK_sparseVect.pl' '$data_fasta' '$gspan_file'  $max_rad $max_dist_relations

]]>
	</command>
	<inputs>
		<param type="data" name="gspan_file" format="searchgui_archive"  />
		<param type="data" name="data_fasta" format="fasta" />
		<param name="max_rad" type="integer" value="3" size="5" label="maximum radius " help="-R"/>
		<param name="max_dist_relations" type="integer" value="3" size="5" label="maximum distance relations" help="-D"/>
	</inputs>
	<outputs>
		<data name="data_svector" format="zip" from_work_dir="SVECTOR/data.svector" label="data_svector"/>
	</outputs>
	<tests>
		<test>
			<param name="data_fasta" value="data.fasta"/>
			<param name="gspan_file" value="1.group.gspan.bz2" ftype="searchgui_archive"/>
			<param name="max_rad" value="3"/>
			<param name="max_dist_relations" value="3"/>
			<output name="data_svector" file="SVECTOR/data.svector" ftype="zip" />
		</test>
	</tests>
	<help>
		<![CDATA[

**What it does**

Produces an explicit sparse feature encoding.
Integer code for the invariant graph encoding is used as a feature indicator. In this way,
the integer associated to each feature (i.e. each pair or neighborhood subgraphs of radius r whose
roots are at distance d) can be interpreted as the feature key and the (normalized) count of occurrences as its value.
This allows to obtain an explicit feature encoding for a given graph G as a sparse vector in ℝ^m (with a very high dimension m).

**Parameters**

+	**-R** <max radius> (default: 1)
+	**-D** <max distance relations> (default: 4)


    ]]>
	</help>
	<citations>
		<citation type="doi">10.1093/bioinformatics/bts224</citation>
		<citation type="bibtex">@inproceedings{costa2010fast,
      title={Fast neighborhood subgraph pairwise distance kernel},
      author={Costa, Fabrizio and De Grave, Kurt},
      booktitle={Proceedings of the 26th International Conference on Machine Learning},
      pages={255--262},
      year={2010},
      organization={Omnipress}
    }
	</citation>
	</citations>
</tool>