import Orange from Orange.bio import dicty, geneset, gsea, gene dbc = dicty.DictyExpress() data = dbc.get_data(sample='pkaC-', time="8") #select the first chip (the first attribute) data = data.translate([data.domain.attributes[0]], True) matcher = gene.matcher([[gene.GMKEGG("dicty"), gene.GMDicty()]]) genesets = geneset.collections((("KEGG",), "dicty")) res = gsea.direct(data, matcher=matcher, min_part=0.05, gene_sets=genesets) print "%-40s %6s %6s %6s %7s" % ("LABEL", "NES", "P-VAL", "SIZE", "MATCHED") for name,resu in sorted(res.items()[:10], key=lambda x: x[1]["p"]): print "%-40s %6.3f %6.3f %6d %7d" % (name.name[:35], resu["nes"], resu["p"], resu["size"], resu["matched_size"])
import Orange from Orange.bio import dicty, geneset, gsea, gene, geo gds = geo.GDS("GDS10") data = gds.getdata() matcher = gene.matcher([gene.GMKEGG("H**o sapiens")]) genesets = geneset.collections((("KEGG",), "H**o sapiens")) # the number of permutations (n) should be much higher res = gsea.run( data, gene_sets=genesets, matcher=matcher, min_part=0.05, permutation="phenotype", n=10, phen_desc="tissue", gene_desc="gene", ) print print "GSEA results (descriptor: tissue)" print "%-40s %6s %6s %6s %7s" % ("LABEL", "NES", "FDR", "SIZE", "MATCHED") for gs, resu in sorted(res.items(), key=lambda x: x[1]["fdr"])[:10]: print "%-40s %6.3f %6.3f %6d %7d" % (gs.name[:30], resu["nes"], resu["fdr"], resu["size"], resu["matched_size"])
import Orange from Orange.bio import dicty, geneset, gsea, gene, geo gds = geo.GDS("GDS10") data = gds.getdata() matcher = gene.matcher([gene.GMKEGG("H**o sapiens")]) genesets = geneset.collections((("KEGG", ), "H**o sapiens")) #the number of permutations (n) should be much higher res = gsea.run(data, gene_sets=genesets, matcher=matcher, min_part=0.05, permutation="phenotype", n=10, phen_desc="tissue", gene_desc="gene") print print "GSEA results (descriptor: tissue)" print "%-40s %6s %6s %6s %7s" % ("LABEL", "NES", "FDR", "SIZE", "MATCHED") for gs, resu in sorted(res.items(), key=lambda x: x[1]["fdr"])[:10]: print "%-40s %6.3f %6.3f %6d %7d" % (gs.name[:30], resu["nes"], resu["fdr"], resu["size"], resu["matched_size"])