def get_pvalue(List1, List2):
star = []
ps = PyStats()
for i in range(len(List1)):
p = ps.fisher_test([List1[i], List2[i], (List1[i] + List2[i]) / 2.0, (List1[i] + List2[i]) / 2.0])
if p < 10e-6:
star.append("***")
elif p < 0.0001:
star.append("**")
elif p < 0.01:
star.append("*")
else:
star.append("")
return star
def get_pvalue(List1, List2):
star = []
ps = PyStats()
for i in range(len(List1)):
p = ps.fisher_test([
List1[i], List2[i], (List1[i] + List2[i]) / 2.0,
(List1[i] + List2[i]) / 2.0
])
if p < 10e-6:
star.append('***')
elif p < 0.0001:
star.append('**')
elif p < 0.01:
star.append('*')
else:
star.append('')
return star
G[fields[0]]=1
inFile.close()
'''
for k in D :
print(k)
print(D[k])
for k in D2 :
print(k)
print(D2[k])
'''
from PyStats.PyStatsClass import PyStats
ps = PyStats()
ouFile = open('16s.12s.tumor.normal.sv.exome','w')
D3 = dict()
for k in G:
#ouFile.write(k+'\t')
#ouFile.write(str(D.get(k,[0,0])[0]+D2.get(k,[0,0])[0])+'\t')
#ouFile.write(str(D.get(k,[0,0])[1]+D2.get(k,[0,0])[1])+'\n')
D3.setdefault(k,[0,0,-1])
D3[k][0] = D.get(k,[0,0])[0]+D2.get(k,[0,0])[0]
D3[k][1] = D.get(k,[0,0])[1]+D2.get(k,[0,0])[1]
D3[k][2] = ps.fisher_test([20,8,D3[k][0],D3[k][1]])
#for k in D3:
# print(D3[k])
d = D3.items()
G[fields[0]] = 1
inFile.close()
'''
for k in D :
print(k)
print(D[k])
for k in D2 :
print(k)
print(D2[k])
'''
from PyStats.PyStatsClass import PyStats
ps = PyStats()
ouFile = open('16s.12s.tumor.normal.sv.exome', 'w')
D3 = dict()
for k in G:
#ouFile.write(k+'\t')
#ouFile.write(str(D.get(k,[0,0])[0]+D2.get(k,[0,0])[0])+'\t')
#ouFile.write(str(D.get(k,[0,0])[1]+D2.get(k,[0,0])[1])+'\n')
D3.setdefault(k, [0, 0, -1])
D3[k][0] = D.get(k, [0, 0])[0] + D2.get(k, [0, 0])[0]
D3[k][1] = D.get(k, [0, 0])[1] + D2.get(k, [0, 0])[1]
D3[k][2] = ps.fisher_test([20, 8, D3[k][0], D3[k][1]])
#for k in D3:
# print(D3[k])
d = D3.items()
