def fetch_string_ppi_edges():
go_edges = {}
grid_len = 0
if constants.USE_CACHE:
if os.path.isfile(
os.path.join(constants.DICTIONARIES_DIR,
"GO_edges_ppi_total.txt")):
print "about to load ppi"
GO_edges_ppi_grid = infra.load_phenotype_data(
"GO_edges_ppi_total.txt",
phenotype_list_path=constants.DICTIONARIES_DIR)
grid_len = len(GO_edges_ppi_grid)
print "done load ppi ({} lines). about to load to dict".format(
grid_len)
for cur in GO_edges_ppi_grid:
go_edges[cur[0]] = int(cur[1])
print "done load to dict"
return go_edges
print "fetching ensg"
ensg_dict = get_ensg_dict()
print "fetching ensp"
ensp_dict = get_ensp_dict()
print "fetching string ppi"
string_ppi_dict = get_string_ppi_dict()
go_edges = {}
count = 0
for cur_edge, cur_score in string_ppi_dict.iteritems():
count += 1
print count
vertices = cur_edge.split("=")
if not ensp_dict.has_key(vertices[0]) or not ensp_dict.has_key(
vertices[1]):
continue
go_src = ensp_dict[vertices[0]]["GO Terms"]
go_dst = ensp_dict[vertices[1]]["GO Terms"]
for cur_src in go_src:
for cur_dst in go_dst:
edge = "{}={}".format(cur_src, cur_dst)
edge_alt = "{}={}".format(cur_dst, cur_src)
if go_edges.has_key(edge):
go_edges[edge] += int(cur_score)
elif go_edges.has_key(edge_alt):
go_edges[edge_alt] += int(cur_score)
else:
go_edges[edge] = int(cur_score)
with file(
os.path.join(constants.OUTPUT_GLOBAL_DIR,
"GO_edges_ppi_total.txt"), "w+") as f:
count = 0
for k, v in go_edges.iteritems():
count += 1
print "{}/{}".format(count, grid_len)
f.write("{}\t{}\n".format(k, v))
return go_edges
def fetch_ppi_edges():
ensg_dict = get_ensg_dict()
ensp_dict = get_ensp_dict()
string_ppi_dict = get_string_ppi_dict()
for k,v in string_ppi_dict.iteritems():
cur_vertices = k.split("=")
if ensp_dict.has_key(cur_vertices[0]) and ensp_dict.has_key(cur_vertices[1]):
go_src = ensp_dict.has_key(cur_vertices[0])["GO Terms"]
go_dest = ensp_dict.has_key(cur_vertices[1])["GO Terms"]
string_ppi_go_edges = {}
for cur_go_src in go_src:
for cur_go_dest in go_dest:
cur_edge = "{}={}".format(cur_go_src, cur_go_dest)
if string_ppi_go_edges.has_key(cur_edge):
string_ppi_go_edges[cur_edge]+=v
else:
string_ppi_go_edges[cur_edge]=v
return string_ppi_go_edges
def fetch_string_ppi_edges():
go_edges = {}
if constants.USE_CACHE:
if os.path.isfile(os.path.join(constants.DICTIONARIES_DIR,"GO_edges_ppi_total.txt")):
GO_edges_ppi_grid = infra.load_phenotype_data("GO_edges_ppi_total.txt",phenotype_list_path=constants.DICTIONARIES_DIR)
for cur in GO_edges_ppi_grid:
go_edges[cur[0]] = int(cur[1])
return go_edges
print "fetching ensg"
ensg_dict = get_ensg_dict()
print "fetching ensp"
ensp_dict = get_ensp_dict()
print "fetching string ppi"
string_ppi_dict = get_string_ppi_dict()
go_edges = {}
count = 0
for cur_edge, cur_score in string_ppi_dict.iteritems():
count +=1
print count
vertices = cur_edge.split("=")
if not ensp_dict.has_key(vertices[0]) or not ensp_dict.has_key(vertices[1]): continue
go_src = ensp_dict[vertices[0]]["GO Terms"]
go_dst = ensp_dict[vertices[1]]["GO Terms"]
for cur_src in go_src:
for cur_dst in go_dst:
edge = "{}={}".format(cur_src,cur_dst)
edge_alt = "{}={}".format(cur_dst, cur_src)