def stEvalInfo(d1, d2, bg):
""" Compute Match,Pval between d1 & d2.
Return as string. """
match = utils_graph.intersectLists([d1, d2])
pval = utils_stats.prob3(len(bg.keys()),
len(d1.keys()),
len(d2.keys()),
len(match.keys()))
return str(len(d1.keys())) + '\t' + str(len(match.keys())) + '\t' + str(pval)
def getEnrichedClusters(gmeans_clusters, target_sets, background_genes, pval_cut):
""" Return {} of cluster_id to [enriched_cat, enriched_genes {}, pval]
target_sets is {} of cat to genes.
"""
# check to make sure everything is in background
for cluster in gmeans_clusters.keys():
for gene in gmeans_clusters[cluster].keys():
if not background_genes.has_key(gene):
print 'cluster gene not in background genes'
sys.exit(0)
for target in target_sets.keys():
for gene in target_sets[target].keys():
if not background_genes.has_key(gene):
print 'target set gene not in background genes'
sys.exit(0)
ret_clusters = {}
background_len = len(background_genes.keys())
for a_set in target_sets.keys():
target_genes = target_sets[a_set]
target_len = len(target_genes.keys())
for cluster in gmeans_clusters.keys():
cluster_genes = gmeans_clusters[cluster]
cluster_len = len(cluster_genes.keys())
match_genes = utils_graph.intersectLists([cluster_genes,
target_genes])
match_len = len(match_genes.keys())
pval = utils_stats.prob3(background_len,
cluster_len,
target_len,
match_len)
if pval < pval_cut:
if not ret_clusters.has_key(cluster):
ret_clusters[cluster] = {}
cluster_per = int(float(100)*float(match_len)/float(cluster_len))
target_per = int(float(100)*float(match_len)/float(target_len))
ret_clusters[cluster][a_set] = [match_genes, cluster_per, target_per, pval]
return ret_clusters
if hhe_vp2hp.has_key(vp):
hhe = utils_graph.intersectLists([hhe_vp2hp[vp], all_hps])
hhe_len = len(hhe.keys())
preds = pred2vp2hp[predtype][vp]
preds_len = len(preds.keys())
match = utils_graph.intersectLists([hhe, preds])
match_len = len(match.keys())
precision = int(round(float(100) * float(match_len) / float(preds_len)))
if hhe_len > 0:
recall = int(round(float(100) * float(match_len) / float(hhe_len)))
else:
recall = "NA"
random_precision = int(round(float(100) * float(hhe_len) / float(len(all_hps.keys()))))
if match_len != 0:
pval = utils_stats.prob3(len(all_hps.keys()), preds_len, hhe_len, match_len)
else:
pval = "No Matches"
fout.write(
predtype
+ "\t"
+ vp
+ "\t"
+ str(hhe_len)
+ "\t"
+ str(preds_len)
+ "\t"
+ str(match_len)
+ "\t"
+ str(precision)
+ "\t"
