import Orange from orangecontrib.bio import dicty, geneset, gsea, gene, geo gds = geo.GDS("GDS10") data = gds.getdata(transpose=True) 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=data.domain["tissue"], gene_desc=True) 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 orangecontrib.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 orangecontrib.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 orangecontrib.bio import dicty, geneset, gsea, gene, geo gds = geo.GDS("GDS10") data = gds.getdata(transpose=True) 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=data.domain["tissue"], gene_desc=True) 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"])