Mercurial > repos > rnateam > graphclust_nspdk
view NSPDK_candidateClusters.xml @ 8:90da74fd1c5c draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/GraphClust/NSPDK commit 4406735e44aba20859c252be39f4e99df28c7a92
author | rnateam |
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date | Sat, 27 Oct 2018 13:26:33 -0400 |
parents | 25fd145b498a |
children | 1b142e88d068 |
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<tool id="NSPDK_candidateClust" name="NSPDK_candidateClusters" version="9.2.3" > <requirements> <requirement type="package" version="0.6.0">graphclust-wrappers</requirement> <requirement type="package" version="9.2" >nspdk</requirement> </requirements> <stdio> <exit_code range="1:" /> </stdio> <command> <![CDATA[ mkdir ./SVECTOR && #for $ins in $data_svector: ln -f -s '$ins' ./SVECTOR/$ins.element_identifier && #end for NSPDK_candidateClusters.pl '$data_fasta' '$data_names' $noCache $ensf $oc $usn $knn $nhf $nspdk_nhf_max $nspdk_nhf_step $GLOBAL_num_clusters $max_rad $max_dist_relations #if $iteration_num.iteration_num_selector: $iteration_num.CI '$blacklist' '$final_partition_soft' '$fast_cluster_last_round' $iteration_num.GLOBAL_hit_blacklist_overlap #end if ]]> </command> <inputs> <param type="data" name="data_svector" format="zip" multiple="True"/> <param type="data" name="data_fasta" format="fasta" /> <param type="data" name="data_names" format="txt" /> <conditional name="iteration_num"> <param name="iteration_num_selector" type="boolean" checked="no" label="Multiple iterations" help="for single iteration- NO, for multiple-YES"/> <when value="true"> <param name="CI" type="integer" value="2" size="5" label="Number of current iteration "/> <param type="data" name="blacklist" format="txt" /> <param type="data" name="final_partition_soft" format="txt" /> <param type="data" name="fast_cluster_last_round" format="txt" /> <param name="GLOBAL_hit_blacklist_overlap" type="float" value="0.2" size="5" label="Blacklist hit overlap" /> </when> <when value="false" > <param name="CI" type="hidden" value="1" size="5" label="Number of current iteration "></param> </when> </conditional> <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"/> <param name="noCache" truevalue="-no-cache" falsevalue="" checked="True" type="boolean" label="Deactivate caching of kernel value computation (-no-cache)" help="to minimize memory usage"/> <param name="ensf" type="integer" value="5" size="5" label="eccess neighbour size factor" help="-ensf"/> <param name="usn" truevalue="-usn" falsevalue="" checked="True" type="boolean" label="Use shared neighbourhood to weight center density (-usn)" help="by default true"/> <param name="oc" truevalue="-oc" falsevalue="" checked="True" type="boolean" label=" flag to output clusters (-oc)" help="by default true"/> <param name="knn" type="integer" value="20" size="5" label="Number of nearest neighbors" help="-knn num"/> <param name="nhf" type="integer" value="500" size="5" label="Number of hash functions " help="-nhf num"/> <param name="nspdk_nhf_max" type="integer" value="1000" size="5" label="Maximal number of hash functions " /> <param name="nspdk_nhf_step" type="integer" value="25" size="5" label="Size of step for increasing hash functions " help="The number of hash functions is increased by this value after each iteration."/> <param name="GLOBAL_num_clusters" type="integer" value="100" size="5" label="Maxinum number of clusters " /> </inputs> <outputs> <data name="fast_cluster" format="txt" from_work_dir="SVECTOR/data.svector.1.fast_cluster" label="fast_cluster.1" > <filter> iteration_num['iteration_num_selector'] is False</filter> </data> <data name="fast_cluster_sim" format="txt" from_work_dir="SVECTOR/data.svector.1.fast_cluster_sim" label="fast_cluster_sim.1" > <filter> iteration_num['iteration_num_selector'] is False </filter> </data> <data name="black_list" format="txt" from_work_dir="SVECTOR/data.svector.blacklist.1" label="blacklist.1" > <filter> iteration_num['iteration_num_selector'] is False </filter> </data> <data name="fast_cluster_m" format="txt" from_work_dir="SVECTOR/data.svector.*.fast_cluster" label="fast_cluster.$iteration_num.CI" > <filter> iteration_num['iteration_num_selector'] is True</filter> </data> <data name="fast_cluster_sim_m" format="txt" from_work_dir="SVECTOR/data.svector.*.fast_cluster_sim" label="fast_cluster_sim.$iteration_num.CI" > <filter> iteration_num['iteration_num_selector'] is True</filter> </data> <data name="black_list_m" format="txt" from_work_dir="SVECTOR/data.svector.blacklist.*" label="blacklist.$iteration_num.CI" > <filter> iteration_num['iteration_num_selector'] is True</filter> </data> </outputs> <tests> <test> <param name="data_fasta" value="data.fasta"/> <param name="data_names" value="data.names"/> <param name="data_svector" value="1.data.gspan" ftype="zip" /> <conditional name="iteration_num"> <param name="iteration_num_selector" value="false"/> </conditional> <param name="noCache" value="-no-cache"/> <param name="ensf" value="5"/> <param name="oc" value="-oc"/> <param name="max_rad" value="3"/> <param name="max_dist_relations" value="3"/> <param name="usn" value="-usn"/> <param name="knn" value="20"/> <param name="nhf" value="500"/> <param name="nspdk_nhf_max" value="1000"/> <param name="nspdk_nhf_step" value="25"/> <param name="GLOBAL_num_clusters" value="100"/> <output name="fast_cluster" file="SVECTOR/data.svector.1.fast_cluster" /> <output name="fast_cluster_sim" file="SVECTOR/data.svector.1.fast_cluster_sim" /> <output name="black_list" file="SVECTOR/data.svector.blacklist.1" /> </test> </tests> <help> <![CDATA[ **What it does** Copmutes global feature index and returns top dense sets. The candidate clusters are chosen as the top ranking neighborhoods provided that the size of their overlap is below a specified threshold. For more information see *Fast neighborhood subgraph pairwise distance kernel* paper. **Parameters** + **-knn** : <num nearest neighbors> (default: 10) + **-otknn** : flag to output true (i.e. implies full kernel matrix evaluation) k-nearest neighburs (default: 0) + **-oc** : flag to output clusters (default: 0) + **-nhf** : <num hash functions> for the Locality Sensitive Hashing function (default: 250) + **-ensf** : <eccess neighbour size factor> (default: 10) (0 to avoid trimming) + **-usn** : use shared neighbourhood to weight center density (default: 0) ]]> </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>