def read_pickle_write_to_file(summary_fullpath,
chr_list,
fnames_dic,
filter_events=False):
'''
Open a summary textfile, then individually open a pickle and write the
contents to file.
'''
# Get keynames found in pickle file.
# Each keyname will be a row written to file.
_, psi_median_str, log_score_str, sample_name_str, \
counts_00_str, counts_10_str, counts_01_str, counts_11_str, \
assigned_counts_0_str, assigned_counts_1_str, \
percent_accepted_str, group_str, pval_str, event_str \
= get_psi_dic_keynames(full_keynames=True)
writecount = 0
with open(summary_fullpath, 'wb') as writefile:
writer = csv.writer(writefile, delimiter='\t')
# Write header
header = [
event_str, pval_str, sample_name_str, group_str, counts_00_str,
counts_10_str, counts_01_str, counts_11_str, assigned_counts_0_str,
assigned_counts_1_str, psi_median_str, percent_accepted_str,
log_score_str
]
writer.writerow(header)
for chromo in chr_list:
pickle_fullpath_list = fnames_dic[chromo]
for pickle_path in pickle_fullpath_list:
psi_info_dic = read_pickle(pickle_path)
if filter_events == True:
'''
Filter events. If pval == 'NA', then
skip the pickle file and go to the next one.
'''
if 'NA' in psi_info_dic[pval_str]:
continue
row = []
for key in header:
'''
# Dic contains both lists and strings.
But we want to only have one column per
keyvalue. Therefore, we collapse lists
into comma separated values (CSV).
'''
if len(psi_info_dic[key]) == 1:
row.append(psi_info_dic[key][0])
elif len(psi_info_dic[key]) > 1:
# Convert each element in list to string
# so we can join it by commas.
psi_info_dic[key] = [str(i) for i in psi_info_dic[key]]
row.append(','.join(psi_info_dic[key]))
writer.writerow(row)
writecount += 1
return writecount
def read_pickle_write_to_file(summary_fullpath, chr_list, fnames_dic, filter_events=False):
'''
Open a summary textfile, then individually open a pickle and write the
contents to file.
'''
# Get keynames found in pickle file.
# Each keyname will be a row written to file.
_, psi_median_str, log_score_str, sample_name_str, \
counts_00_str, counts_10_str, counts_01_str, counts_11_str, \
assigned_counts_0_str, assigned_counts_1_str, \
percent_accepted_str, group_str, pval_str, event_str \
= get_psi_dic_keynames(full_keynames=True)
writecount = 0
with open(summary_fullpath, 'wb') as writefile:
writer = csv.writer(writefile, delimiter='\t')
# Write header
header = [event_str, pval_str, sample_name_str, group_str,
counts_00_str, counts_10_str, counts_01_str,
counts_11_str, assigned_counts_0_str,
assigned_counts_1_str, psi_median_str, percent_accepted_str,
log_score_str]
writer.writerow(header)
for chromo in chr_list:
pickle_fullpath_list = fnames_dic[chromo]
for pickle_path in pickle_fullpath_list:
psi_info_dic = read_pickle(pickle_path)
if filter_events==True:
'''
Filter events. If pval == 'NA', then
skip the pickle file and go to the next one.
'''
if 'NA' in psi_info_dic[pval_str]:
continue
row = []
for key in header:
'''
# Dic contains both lists and strings.
But we want to only have one column per
keyvalue. Therefore, we collapse lists
into comma separated values (CSV).
'''
if len(psi_info_dic[key]) == 1:
row.append(psi_info_dic[key][0])
elif len(psi_info_dic[key]) > 1:
# Convert each element in list to string
# so we can join it by commas.
psi_info_dic[key] = [str(i) for i in psi_info_dic[key]]
row.append(','.join(psi_info_dic[key]))
writer.writerow(row)
writecount += 1
return writecount
def main():
if len(sys.argv) < 2:
print('Pickle file from t_test_miso_output.py and output '\
'.txt filename must be specified in command line.')
sys.exit()
pickle_path = sys.argv[1]
writefile_path = sys.argv[2]
chr_list = create_chromo_list()
# Read pickle file to get fnames_dic
# This only contains filenames, no data.
fnames_dic = read_pickle(pickle_path)
# Read and write to file.
read_pickle_write_to_file(writefile_path, chr_list, fnames_dic,
filter_events=False)
print('Summary file saved in: %s' %writefile_path)
def main():
if len(sys.argv) < 2:
print('Pickle file from t_test_miso_output.py and output '\
'.txt filename must be specified in command line.')
sys.exit()
pickle_path = sys.argv[1]
writefile_path = sys.argv[2]
chr_list = create_chromo_list()
# Read pickle file to get fnames_dic
# This only contains filenames, no data.
fnames_dic = read_pickle(pickle_path)
# Read and write to file.
read_pickle_write_to_file(writefile_path,
chr_list,
fnames_dic,
filter_events=False)
print('Summary file saved in: %s' % writefile_path)
def main():
parser = OptionParser()
parser.add_option('-1', '--group1_file', dest='group_1_samplenames_file',
help='Filename containing group 1 sample names (PCa)')
parser.add_option('-2', '--group2_file', dest='group_2_samplenames_file',
help='Filename containing group 2 sample names (NEPC)')
parser.add_option('-d', '--main_directory', dest='main_dir',
help='Main directory containing miso output results.')
parser.add_option('-o', '--output_directory', dest='output_dir',
help='Output directory of t-test results.')
parser.add_option('-O', '--output_filename', dest='output_fname',
help='Output filename of the t-test results.')
parser.add_option('-m', '--min_counts', type='int', dest='min_counts',
help='Minimum junction read counts to be considered '\
'into the t-test. Best practices says 10.')
# Parse options
(options, _) = parser.parse_args()
# Define constants from options
group_1_samplenames_file = options.group_1_samplenames_file
group_2_samplenames_file = options.group_2_samplenames_file
main_dir = options.main_dir
output_dir = options.output_dir
output_fname = options.output_fname
min_counts = options.min_counts
# Define constants
summary_fullpath = os.path.join(output_dir, output_fname)
# Get sample names from textfile.
group_1_samples = get_sample_names_from_file(group_1_samplenames_file)
group_2_samples = get_sample_names_from_file(group_2_samplenames_file)
# Create list of chromosomes.
chr_list = create_chromo_list(prefix='chr')
# chr_list = ['chr11']
# Subset list for only those that contain miso outputs.
group_1_samples = check_if_empty_dir(main_dir, group_1_samples, chr_list)
group_2_samples = check_if_empty_dir(main_dir, group_2_samples, chr_list)
# Init fnames dic
fnames_dic = {}
# Run on multiple threads.
q = Queue()
process_list = []
for chromo in chr_list:
print('Sending %s job to core...' %chromo)
p = Process(target=t_test_and_pickle,
args=(fnames_dic, chromo, output_dir,
group_1_samples, group_2_samples,
main_dir, q, min_counts))
process_list.append(p)
p.start()
for chromo in chr_list:
fnames_dic.update(q.get())
# Wait for all threads to be done before continuing.
for p in process_list:
p.join()
print('Completed %s jobs.' %len(chr_list))
# Write fnames_dic as pickle file.
pickle_filename = ''.join([output_fname, '_filenames_dic.pickle'])
fnames_savepath = os.path.join(output_dir, pickle_filename)
print('Saving filenames_dic.pickle to %s' %fnames_savepath)
pickle_path = save_dic_as_pickle(fnames_dic, fnames_savepath)
# Write information from pickle to textfile.
print('Writing information from pickle to textfile.')
# Read pickle file to get fnames_dic
fnames_dic = read_pickle(pickle_path)
# Read and write to file.
read_pickle_write_to_file(summary_fullpath, chr_list, fnames_dic,
filter_events=True)
print('Summary file saved in: %s' %summary_fullpath)
def main():
parser = OptionParser()
parser.add_option('-1',
'--group1_file',
dest='group_1_samplenames_file',
help='Filename containing group 1 sample names (PCa)')
parser.add_option('-2',
'--group2_file',
dest='group_2_samplenames_file',
help='Filename containing group 2 sample names (NEPC)')
parser.add_option('-d',
'--main_directory',
dest='main_dir',
help='Main directory containing miso output results.')
parser.add_option('-o',
'--output_directory',
dest='output_dir',
help='Output directory of t-test results.')
parser.add_option('-O',
'--output_filename',
dest='output_fname',
help='Output filename of the t-test results.')
parser.add_option('-m', '--min_counts', type='int', dest='min_counts',
help='Minimum junction read counts to be considered '\
'into the t-test. Best practices says 10.')
# Parse options
(options, _) = parser.parse_args()
# Define constants from options
group_1_samplenames_file = options.group_1_samplenames_file
group_2_samplenames_file = options.group_2_samplenames_file
main_dir = options.main_dir
output_dir = options.output_dir
output_fname = options.output_fname
min_counts = options.min_counts
# Define constants
summary_fullpath = os.path.join(output_dir, output_fname)
# Get sample names from textfile.
group_1_samples = get_sample_names_from_file(group_1_samplenames_file)
group_2_samples = get_sample_names_from_file(group_2_samplenames_file)
# Create list of chromosomes.
chr_list = create_chromo_list(prefix='chr')
# chr_list = ['chr11']
# Subset list for only those that contain miso outputs.
group_1_samples = check_if_empty_dir(main_dir, group_1_samples, chr_list)
group_2_samples = check_if_empty_dir(main_dir, group_2_samples, chr_list)
# Init fnames dic
fnames_dic = {}
# Run on multiple threads.
q = Queue()
process_list = []
for chromo in chr_list:
print('Sending %s job to core...' % chromo)
p = Process(target=t_test_and_pickle,
args=(fnames_dic, chromo, output_dir, group_1_samples,
group_2_samples, main_dir, q, min_counts))
process_list.append(p)
p.start()
for chromo in chr_list:
fnames_dic.update(q.get())
# Wait for all threads to be done before continuing.
for p in process_list:
p.join()
print('Completed %s jobs.' % len(chr_list))
# Write fnames_dic as pickle file.
pickle_filename = ''.join([output_fname, '_filenames_dic.pickle'])
fnames_savepath = os.path.join(output_dir, pickle_filename)
print('Saving filenames_dic.pickle to %s' % fnames_savepath)
pickle_path = save_dic_as_pickle(fnames_dic, fnames_savepath)
# Write information from pickle to textfile.
print('Writing information from pickle to textfile.')
# Read pickle file to get fnames_dic
fnames_dic = read_pickle(pickle_path)
# Read and write to file.
read_pickle_write_to_file(summary_fullpath,
chr_list,
fnames_dic,
filter_events=True)
print('Summary file saved in: %s' % summary_fullpath)
