def motif_enrich(mgdict, genes, adj_p=True):
# Number of genes with motifs mapped
M = len(set(itertools.chain.from_iterable(mgdict.values())))
enrich = []
run_count = 0
# For each motif...
for mid in mgdict.iterkeys():
m = set(mgdict[mid])
a = len(m.intersection(genes))
b = len(m - genes)
c = len(genes - m)
d = M - len(m.union(genes))
if a < 2: continue
run_count += 1
fentry = np.array([[a, b], [c, d]])
try:
odds, p = fisher_exact(fentry)
except ValueError:
print '<h3>ValueError</h3>'
print '<p>An error in the motif enrichment function has occured</p>'
print '<p>Please <a href="mailto:[email protected]">notify the administrator</a>.</p>'
print M, len(m), len(genes), a, d
sys.exit(1)
#TODO: Only overrepresentation at the moment
if odds > 1:
enrich.append([mid, p, odds, fentry])
# Adjust p-values
if adj_p:
padj = padjust.fdr([x[1] for x in enrich])
for i, q in zip(xrange(len(enrich)), padj):
enrich[i][1] = q
enrich = sorted(enrich, key=lambda x: x[1])
return enrich
def calc_enrichment(genes, go, set_p, set_m, set_c, underrep=False, adj_p=True):
goenrich = []
np.seterr(all='ignore')
run_count = 0
for go, v in go.iteritems():
GOS = set()
if v[1].lower() == 'biological process': GOS = set_p
elif v[1].lower() == 'molecular function': GOS = set_m
elif v[1].lower() == 'cellular component': GOS = set_c
# The set of genes annotated to the specific GO term
X = v[0]
# The GO-annotated part of the gene set for which we want enrichment
Sgo = genes & GOS
a = len(Sgo & X) # # of our genes in this term
b = len(Sgo - X) # # of our genes NOT in this term
c = len(X - Sgo) # # of genes in the annotated set NOT part of our genes
# of genes in GO category not in our genes or in the specific category
d = len(GOS - X - Sgo)
if a < 2: continue
run_count += 1
fentry = np.array([[a, c], [b, d]], dtype='float64')
odds, p = stats.fisher_exact(fentry)
if underrep and odds < 1:
goenrich.append([go, p, odds, fentry, v[1]])
elif not underrep and odds > 1:
goenrich.append([go, p, odds, fentry, v[1]])
if adj_p:
padj = padjust.fdr([x[1] for x in goenrich])
for i, q in zip(xrange(len(goenrich)), padj):
goenrich[i][1] = q
return sorted(goenrich, key=lambda x: x[1])
