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"])
