def test_mantel(self):
"""mantel should be significant for same matrix, not for random"""
a = reshape(arange(25), (5,5))
b = a.copy()
b[-1,-1] = 26 #slight change
m = mantel(a, b, 1000)
#closely related -- should be significant
assert m < 0.05
c = reshape(ones(25), (5,5))
c[-1,-1] = 3
#not related -- should not be significant
m = mantel(a,c,1000)
assert m > 0.3, m
def test_mantel(self):
"""mantel should be significant for same matrix, not for random"""
a = reshape(arange(25), (5, 5))
b = a.copy()
b[-1, -1] = 26 #slight change
m = mantel(a, b, 1000)
#closely related -- should be significant
assert m < 0.05
c = reshape(ones(25), (5, 5))
c[-1, -1] = 3
#not related -- should not be significant
m = mantel(a, c, 1000)
assert m > 0.3, m
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
sample_id_map_fp = opts.sample_id_map_fp
if sample_id_map_fp:
sample_id_map = dict([(k,v[0]) \
for k,v in fields_to_dict(open(sample_id_map_fp, "U")).items()])
else:
sample_id_map = None
input_dm_fps = opts.input_dms.split(',')
output_f = open(opts.output_fp,'w')
output_f.write(comment)
output_f.write('DM1\tDM2\tNumber of entries\tMantel p-value\n')
num_iterations = opts.num_iterations
for i,fp1 in enumerate(input_dm_fps):
for fp2 in input_dm_fps[i+1:]:
(dm1_labels, dm1), (dm2_labels, dm2) =\
make_compatible_distance_matrices(parse_distmat(open(fp1,'U')),
parse_distmat(open(fp2,'U')),
lookup=sample_id_map)
if len(dm1_labels) < 2:
output_f.write('%s\t%s\t%d\tToo few samples\n' % (fp1,fp2,len(dm1_labels)))
continue
p = mantel(dm1,dm2,n=num_iterations)
p_str = format_p_value_for_num_iters(p,num_iterations)
output_f.write('%s\t%s\t%d\t%s\n' % (fp1,fp2,len(dm1_labels),p_str))
output_f.close()