Mercurial > repos > rnateam > graphclust_nspdk

annotate NSPDK_sparseVect.xml @ 4:0625db6b6e45 draft

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author rnateam
date Mon, 13 Mar 2017 18:05:04 -0400
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children 9b5fb987a484
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165fe96228be planemo upload for repository https://github.com/eteriSokhoyan/galaxytools/tree/branchForIterations/tools/GraphClust/NSPDK commit 21aaee40723b5341b4236edeb0e72995c2054053
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1 <tool id="nspdk_sparse" name="NSPDK_sparseVect" version="9.2">
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2 <requirements>
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3 <requirement type="package" version="0.1.10">graphclust-wrappers</requirement>
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4 <requirement type="package" version="9.2">nspdk</requirement>
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5 </requirements>
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6 <stdio>
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7 <exit_code range="1:" />
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8 </stdio>
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9 <command>
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10 <![CDATA[
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13 NSPDK_sparseVect.pl
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14 '$data_fasta'
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15 '$gspan_file'
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16 $max_rad
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17 $max_dist_relations
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19 ]]>
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20 </command>
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21 <inputs>
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22 <param type="data" name="gspan_file" />
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23 <param type="data" name="data_fasta" format="fasta" />
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24 <param name="max_rad" type="integer" value="3" label="maximum radius " help="-R"/>
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25 <param name="max_dist_relations" type="integer" value="3" label="maximum distance relations" help="-D"/>
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26 </inputs>
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27 <outputs>
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28 <data name="data_svector" format="zip" from_work_dir="SVECTOR/data.svector" label="data_svector"/>
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29 </outputs>
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30 <tests>
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31 <test>
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32 <param name="data_fasta" value="data.fasta"/>
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33 <param name="gspan_file" value="1.group.gspan.bz2" ftype="searchgui_archive"/>
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34 <param name="max_rad" value="3"/>
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35 <param name="max_dist_relations" value="3"/>
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36 <output name="data_svector" file="SVECTOR/data.svector" ftype="zip" />
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37 </test>
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38 </tests>
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39 <help>
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40 <![CDATA[
0
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42 **What it does**
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44 Produces an explicit sparse feature encoding.
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45 Integer code for the invariant graph encoding is used as a feature indicator. In this way,
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46 the integer associated to each feature (i.e. each pair or neighborhood subgraphs of radius r whose
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47 roots are at distance d) can be interpreted as the feature key and the (normalized) count of occurrences as its value.
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48 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).
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50 **Parameters**
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51
4
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52 + **-R** <max radius> (default: 1)
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53 + **-D** <max distance relations> (default: 4)
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56 ]]>
4
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57 </help>
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58 <citations>
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59 <citation type="doi">10.1093/bioinformatics/bts224</citation>
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60 <citation type="bibtex">@inproceedings{costa2010fast,
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61 title={Fast neighborhood subgraph pairwise distance kernel},
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62 author={Costa, Fabrizio and De Grave, Kurt},
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63 booktitle={Proceedings of the 26th International Conference on Machine Learning},
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64 pages={255--262},
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65 year={2010},
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66 organization={Omnipress}
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67 }
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68 </citation>
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69 </citations>
0
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70 </tool>