def get_coefficients(run, key):
"""Given a parsed taxa summary table, will find and return correlation coefficients"""
pearson_compare = compare_taxa_summaries(run, key, 'paired', 'pearson')
spearman_compare = compare_taxa_summaries(run, key, 'paired', 'spearman')
pearson_coeff = pearson_compare[2].split('\n')[-2].split()[0]
spearman_coeff = spearman_compare[2].split('\n')[-2].split()[0]
return pearson_coeff, spearman_coeff
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
if len(opts.taxa_summary_fps) != 2:
option_parser.error("Exactly two taxa summary files are required. You "
"provided %d." % len(opts.taxa_summary_fps))
# Create the output dir if it doesn't already exist.
try:
create_dir(opts.output_dir)
except:
option_parser.error("Could not create or access output directory "
"specified with the -o option.")
sample_id_map = None
if opts.sample_id_map_fp:
sample_id_map = parse_sample_id_map(open(opts.sample_id_map_fp, 'U'))
results = compare_taxa_summaries(
parse_taxa_summary_table(open(opts.taxa_summary_fps[0], 'U')),
parse_taxa_summary_table(open(opts.taxa_summary_fps[1], 'U')),
opts.comparison_mode,
correlation_type=opts.correlation_type,
tail_type=opts.tail_type,
num_permutations=opts.num_permutations,
confidence_level=opts.confidence_level,
perform_detailed_comparisons=opts.perform_detailed_comparisons,
sample_id_map=sample_id_map,
expected_sample_id=opts.expected_sample_id)
# Write out the sorted and filled taxa summaries, basing their
# filenames on the original input filenames. If the filenames are the same,
# append a number to each filename.
same_filenames = False
if basename(opts.taxa_summary_fps[0]) == \
basename(opts.taxa_summary_fps[1]):
same_filenames = True
for orig_ts_fp, filled_ts_lines, file_num in zip(opts.taxa_summary_fps,
results[:2], range(0, 2)):
filename_suffix = '_sorted_and_filled'
if same_filenames:
filename_suffix += '_%d' % file_num
filled_ts_fp = add_filename_suffix(orig_ts_fp, filename_suffix)
filled_ts_f = open(join(opts.output_dir, filled_ts_fp), 'w')
filled_ts_f.write(filled_ts_lines)
filled_ts_f.close()
# Write the overall comparison result.
overall_comp_f = open(join(opts.output_dir, 'overall_comparison.txt'), 'w')
overall_comp_f.write(results[2])
overall_comp_f.close()
# Write the correlation vector containing the pairwise sample comparisons.
if opts.perform_detailed_comparisons:
corr_vec_f = open(join(opts.output_dir, 'detailed_comparisons.txt'),
'w')
corr_vec_f.write(results[3])
corr_vec_f.close()
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
if len(opts.taxa_summary_fps) != 2:
option_parser.error("Exactly two taxa summary files are required. You "
"provided %d." % len(opts.taxa_summary_fps))
# Create the output dir if it doesn't already exist.
try:
create_dir(opts.output_dir)
except:
option_parser.error("Could not create or access output directory "
"specified with the -o option.")
sample_id_map = None
if opts.sample_id_map_fp:
sample_id_map = parse_sample_id_map(open(opts.sample_id_map_fp, 'U'))
results = compare_taxa_summaries(
parse_taxa_summary_table(open(opts.taxa_summary_fps[0], 'U')),
parse_taxa_summary_table(open(opts.taxa_summary_fps[1], 'U')),
opts.comparison_mode, correlation_type=opts.correlation_type,
tail_type=opts.tail_type, num_permutations=opts.num_permutations,
confidence_level=opts.confidence_level,
perform_detailed_comparisons=opts.perform_detailed_comparisons,
sample_id_map=sample_id_map,
expected_sample_id=opts.expected_sample_id)
# Write out the sorted and filled taxa summaries, basing their
# filenames on the original input filenames. If the filenames are the same,
# append a number to each filename.
same_filenames = False
if basename(opts.taxa_summary_fps[0]) == \
basename(opts.taxa_summary_fps[1]):
same_filenames = True
for orig_ts_fp, filled_ts_lines, file_num in zip(opts.taxa_summary_fps,
results[:2], range(0, 2)):
filename_suffix = '_sorted_and_filled'
if same_filenames:
filename_suffix += '_%d' % file_num
filled_ts_fp = add_filename_suffix(orig_ts_fp, filename_suffix)
filled_ts_f = open(join(opts.output_dir, filled_ts_fp), 'w')
filled_ts_f.write(filled_ts_lines)
filled_ts_f.close()
# Write the overall comparison result.
overall_comp_f = open(join(opts.output_dir, 'overall_comparison.txt'), 'w')
overall_comp_f.write(results[2])
overall_comp_f.close()
# Write the correlation vector containing the pairwise sample comparisons.
if opts.perform_detailed_comparisons:
corr_vec_f = open(join(opts.output_dir,
'detailed_comparisons.txt'), 'w')
corr_vec_f.write(results[3])
corr_vec_f.close()
