Example: ./script.py <infile> 4,5,8,9,3,6,7,10 <outfile>"""
exit(1)
normalised_data = dict()
f = open(fn)
for row in f:
l = row.strip().split('\t')
if l[0] not in normalised_data:
normalised_data[l[0]] = [map(float,l[1:])]
else:
normalised_data[l[0]] += [map(float,l[1:])]
f.close()
# averaging
normalised_data2 = dict()
for e in normalised_data:
if len(normalised_data[e]) > 1:
no = len(normalised_data[e]) # the number of probesets
normalised_data2[e] = [sum([normalised_data[e][i][j] for i in xrange(no)])/no for j in xrange(8)]
else:
normalised_data2[e] = normalised_data[e][0]
#g = open(ofn,'w')
#for e in normalised_data2:
# print >> g,"\t".join([e]+map(str,normalised_data2[e]))
#g.close()
test_results = statistical_test(normalised_data2,cascon,test_type="unpaired t-test")
dict_to_file(test_results,ofn)
#!/home/paulk/software/bin/python
from __future__ import division
from sys import argv, exit, stderr
from scipy import *
from scipy import stats
from key_functions import statistical_test, dict_to_file
try:
fn = argv[1]
ofn = argv[2]
except IndexError:
print >> stderr, """\
Script to perform a statistical test on columns of data one row at a time.
Performs an unpaired t-test by default. Modify to add tests.
Usage:./script.py <infile> <outfile>"""
exit(1)
cascon = [4, 5, 8, 9, 3, 6, 7, 10]
f = open(fn)
normalised_data = dict()
for row in f:
l = row.strip().split("\t")
normalised_data[l[0], l[1]] = map(float, l[2:])
f.close()
test_results = statistical_test(normalised_data, cascon)
dict_to_file(test_results, ofn)
#!/home/paulk/software/bin/python
from __future__ import division
from sys import argv, exit, stderr
from scipy import *
from scipy import stats
from key_functions import statistical_test, dict_to_file
try:
fn = argv[1]
ofn = argv[2]
except IndexError:
print >> stderr, """\
Script to perform a statistical test on columns of data one row at a time.
Performs an unpaired t-test by default. Modify to add tests.
Usage:./script.py <infile> <outfile>"""
exit(1)
cascon = [4, 5, 8, 9, 3, 6, 7, 10]
f = open(fn)
normalised_data = dict()
for row in f:
l = row.strip().split('\t')
normalised_data[l[0], l[1]] = map(float, l[2:])
f.close()
test_results = statistical_test(normalised_data, cascon)
dict_to_file(test_results, ofn)
f = open(fn)
for row in f:
l = row.strip().split('\t')
if l[0] not in normalised_data:
normalised_data[l[0]] = [map(float, l[1:])]
else:
normalised_data[l[0]] += [map(float, l[1:])]
f.close()
# averaging
normalised_data2 = dict()
for e in normalised_data:
if len(normalised_data[e]) > 1:
no = len(normalised_data[e]) # the number of probesets
normalised_data2[e] = [
sum([normalised_data[e][i][j] for i in xrange(no)]) / no
for j in xrange(8)
]
else:
normalised_data2[e] = normalised_data[e][0]
#g = open(ofn,'w')
#for e in normalised_data2:
# print >> g,"\t".join([e]+map(str,normalised_data2[e]))
#g.close()
test_results = statistical_test(normalised_data2,
cascon,
test_type="unpaired t-test")
dict_to_file(test_results, ofn)
