Input: * a set of upstream sequences in FASTA format * a namespace (a datasource, e.g. Ensembl) * an identifier (optional) Output: * a list of gene sub-clusters See, http://genome.imim.es/webservices/workflows.html page for more details. sequences content org.embl.ebi.escience.scuflworkers.biomoby.ExtractMobyData org.embl.ebi.escience.scuflworkers.biomoby.ExtractMobyData org.embl.ebi.escience.scuflworkers.java.DecodeBase64 org.biomoby.client.taverna.plugin.ExtractMobyData org.embl.ebi.escience.scuflworkers.biomoby.ExtractMobyData org.biomoby.client.taverna.plugin.ExtractMobyData org.biomoby.client.taverna.plugin.ExtractMobyData import java.io.*; import javax.xml.parsers.*; import org.w3c.dom.*; import org.xml.sax.*; import org.apache.xml.serialize.XMLSerializer; String OutObj=""; String skel="<?xml version='1.0' encoding='ISO-8859-1'?><moby:MOBY xmlns:moby='http://www.biomoby.org/moby'><moby:mobyContent><moby:mobyData queryID='one'><moby:Collection moby:articleName=\"matscan_predictions\"></moby:Collection></moby:mobyData></moby:mobyContent></moby:MOBY>"; // String skel="<moby:MOBY xmlns:moby='http://www.biomoby.org/moby'><moby:mobyContent><moby:mobyData queryID='one'><moby:Collection moby:articleName=\"matscan_predictions\"></moby:Collection></moby:mobyData></moby:mobyContent></moby:MOBY>"; // System.err.println ("Filtering MatScan Collection..."); // clusters list processing String[] cluster_identifiers_temp = clusters.split("\n"); ArrayList clusters_identifiers = new ArrayList (); int i = 0; int maxi = cluster_identifiers_temp.length; while (i < maxi) { String cluster = cluster_identifiers_temp[i]; clusters_identifiers.add (cluster); i++; } // MatScan moby collection processing DocumentBuilderFactory dbf=DocumentBuilderFactory.newInstance(); DocumentBuilder db = dbf.newDocumentBuilder(); // input initialisation InputSource Source1 = new InputSource(new StringReader(MatScan)); Document doc1=db.parse(Source1); // output initialisation InputSource SourceSkel = new InputSource(new StringReader(skel)); Document docsalida=db.parse(SourceSkel); NodeList nodelistfinal = docsalida.getElementsByTagName("moby:Collection"); Node comienzo = nodelistfinal.item(0); // serializer initialisation XMLSerializer serializer = new XMLSerializer(); StringWriter sw=new StringWriter(); serializer.setOutputCharStream(sw); NodeList nodelist1bn = doc1.getElementsByTagName("moby:GFF"); // System.err.println ("NodeList global1bn size, " + nodelist1bn.getLength()); NodeList nodelist1b = doc1.getElementsByTagName("GFF"); // System.err.println ("NodeList global1b size, " + nodelist1b.getLength()); NodeList[] globalC={nodelist1bn,nodelist1b}; // Common index variables for all this work int gi; int maxgi; int si; int maxsi; for(gi=0,maxgi=globalC.length;gi<maxgi;gi++) { for (si=0, maxsi=globalC[gi].getLength();si<maxsi;si++) { Node found = globalC[gi].item(si); Node parent = found.getParentNode(); // System.err.println ("found node, " + found.getNodeName() + ", type, " + found.getNodeType()); NamedNodeMap nMap = found.getAttributes (); Node n = nMap.getNamedItem("id"); if (n == null) { n = nMap.getNamedItem ("moby:id"); } String id = ""; if (n == null) { // System.err.println ("error, id is null"); } else { id = n.getNodeValue(); // System.err.println ("id, " + id); } if (clusters_identifiers.contains (id)) { // System.err.println ("clusters_identifiers contains id, " + id); Node changed=docsalida.importNode(parent,true); comienzo.appendChild(changed); } } } // Last step!!! serializer.serialize(docsalida); OutObj = sw.toString(); // Convert it as a List, to be consistent with the current simple to collection Taverna Moby plugin behaviour // filtered_MatScan = OutObj; ArrayList filtered_MatScan = new ArrayList(); filtered_MatScan.add(OutObj); clusters MatScan filtered_MatScan ArrayList list = new ArrayList(); list.add(strings); strings list Runs gff2ps software to vizualize a set of GFF annotations maps. It returns an encoded image in JPEG format. http://moby.ucalgary.ca/moby/MOBY-Central.pl runGFF2JPEG genome.imim.es Converts a FASTA_NA_multi object into a collection of DNASequence moby objects http://moby.ucalgary.ca/moby/MOBY-Central.pl fromFASTAToDNASequenceCollection genome.imim.es Parses a collection of meta-alignment outputs to produce a text-formatted sequence similarity score matrix http://moby.ucalgary.ca/moby/MOBY-Central.pl fromMetaAlignmentsToTextScoreMatrix genome.imim.es a string http://moby.ucalgary.ca/moby/MOBY-Central.pl String runMultiPairwiseMetaAlignment runs Meta-alignment software on a multiple running mode, receiving a collection of maps, making pairs of them and, foreach pair, it produces alignments of sequences of TF binding sites. It returns the predictions in 'Meta-alignment' format. You can use runMatScanGFF to produce the input GFF files http://moby.ucalgary.ca/moby/MOBY-Central.pl runMultiPairwiseMetaAlignment genome.imim.es 0.1 0.5 0.1 Runs Meta-alignment software on a multiple running mode, receiving a collection of maps, making pairs of them and, foreach pair, producing, in GFF format, alignments of sequences of TF binding sites http://moby.ucalgary.ca/moby/MOBY-Central.pl runMultiPairwiseMetaAlignmentGFF genome.imim.es 0.1 0.1 0.5 Reports putative predicted motifs on a given collection of DNA sequences. The motifs collections currently available are Transcription Factor binding site collections. The predicted set of motifs are reported in GFF format. If you want to give MatScan output to Meta-alignment program, you MUST use the 'log-likelihood matrix' mode. http://moby.ucalgary.ca/moby/MOBY-Central.pl runMatScanGFFCollection genome.imim.es log-likelihood Both 0.85 Jaspar Runs SOTA algorithm to partition the gene space into subclusters. The input is a gene score matrix represented as a MicroArrayData_Text object. http://moby.ucalgary.ca/moby/MOBY-Central.pl runSOTAClustering genome.imim.es 35 euclidean Runs Multiple-Meta-Alignment software to perform multiple non-collinear transcription factor map alignments of promoter regions. It returns the multiple-meta-alignment output in GFF format. http://moby.ucalgary.ca/moby/MOBY-Central.pl runMultiMetaAlignmentGFF genome.imim.es 0.1 0.1 0.5 100 -10 Runs Multiple-Meta-Alignment software to perform multiple non-collinear transcription factor map alignments of promoter regions. It returns the multiple-meta-alignment output in meta-alignment text format. http://moby.ucalgary.ca/moby/MOBY-Central.pl runMultiMetaAlignment genome.imim.es 0.5 0.1 100 -10 0.1 Processor to parse the datatype GFF http://moby.ucalgary.ca/moby/MOBY-Central.pl GFF multi_meta_predictions Processor to parse the datatype GFF Processor to parse the datatype Meta_Alignment_Text http://moby.ucalgary.ca/moby/MOBY-Central.pl Meta_Alignment_Text multi_meta_predictions Processor to parse the datatype Meta_Alignment_Text Processor to parse the datatype b64_encoded_jpeg http://moby.ucalgary.ca/moby/MOBY-Central.pl b64_encoded_jpeg image Processor to parse the datatype b64_encoded_jpeg FASTA formatted sequence http://moby.ucalgary.ca/moby/MOBY-Central.pl FASTA_NA_multi text/txt text/txt text/xml image/*