def handleRegionClustering(self, genome, tracks, clusterMethod, extra_option): region_cluster_track = self.getHistoryTrackDef('track1') print region_cluster_track region_ref_track = self.params.get('reftrack1') if region_cluster_track[0] == 'galaxy' : file_type = region_cluster_track[1] track_path = region_cluster_track[2] userBinSource = GalaxyInterface._getUserBinSource('bed', track_path, genome) validFeature = SplittedRegionsAsFeaturesCatalog.getValidAnalyses(genome,region_ref_track,[]) analysisDef = validFeature[0] result = AnalysisDefJob(analysisDef, region_ref_track, [], userBinSource).run() print [result[localKey][validFeature[1]] for localKey in sorted(result.keys())]
def build_feature_vector(genome, ctrack, feature, regSpec, binSpec): ''' this function create a feature vector for ctrack feature specifies how the vector is constructed ''' #print 'Feauter:', LocalResultsAsFeaturesCatalog.getValidAnalyses(genome, ctrack, []) validFeature = LocalResultsAsFeaturesCatalog.getValidAnalyses(genome, ctrack, [])[feature] analysisDef = validFeature[0] #regSpec = self.params.get("region") #binSpec = self.params.get("binsize") userBinSource = GalaxyInterface._getUserBinSource(regSpec,binSpec,genome) result = AnalysisDefJob(analysisDef, ctrack, [], userBinSource).run() return [result[localKey][validFeature[1]] for localKey in sorted(result.keys())]