def __perform_normalization(self, normalization_type, musicc_intra='use_generic'):
""" Normalizes the data in the metagenomic profile of this test block.
"""
mgprofile = self.block.metagenomic_profile
if normalization_type == "relative":
normalization.relative_normalization(mgprofile, self.new_dir)
elif normalization_type == "musicc":
normalization.musicc_normalization(mgprofile, self.block.gen_params['abundance_data'],
self.new_dir, musicc_intra=musicc_intra)
def __perform_normalization(self,
normalization_type,
musicc_intra='use_generic'):
""" Normalizes the data in the metagenomic profile of this test block.
"""
mgprofile = self.block.metagenomic_profile
if normalization_type == "relative":
normalization.relative_normalization(mgprofile, self.new_dir)
elif normalization_type == "musicc":
normalization.musicc_normalization(
mgprofile,
self.block.gen_params['abundance_data'],
self.new_dir,
musicc_intra=musicc_intra)
def main():
""" Main script for running comparative analysis from the command line.
"""
tests, genparams = parse(filename)
# dictionary to hold tests and test results
test_results = dict()
abundance_sep = genparams['abundance_sep']
metadata_sep = genparams['metadata_sep']
abundance_data_path = genparams["abundance_data"]
metadata_path = genparams["sample_metadata"]
metadata_hdr = genparams["metadata_header"]
output_dir = genparams["output_directory"]
lbl = genparams["class_label"]
class_names = genparams["class_names"]
# give each test block a copy of the profile
run_order = list()
master_mp = mgp.metagenomic_profile(abundance_data_path, metadata_path, a_sep=abundance_sep,
m_sep=metadata_sep, metadata_header=metadata_hdr, metadata_label=lbl,
class_names=class_names)
if genparams["normalization"] == "relative":
normalization.relative_normalization(master_mp, output_dir)
elif genparams["normalization"] == "musicc":
normalization.musicc_normalization(master_mp, abundance_data_path, output_dir)
for tb in tests:
tb_class_names = tb.params["class_names"] if "class_names" in list(tb.params.keys()) else genparams["class_names"]
if "class_label" in tb.params:
lbl = tb.params["class_label"]
rules = tb.params["filter_rules"] if "filter_rules" in tb.params else None
labels = tb.params["filter_labels"] if "filter_labels" in tb.params else None
mp = mgp.metagenomic_profile(abundance_data_path, metadata_path, a_sep=abundance_sep,
m_sep=metadata_sep, metadata_header=metadata_hdr, metadata_label=lbl,
class_names=tb_class_names, filter_rules=rules, filter_labels=labels)
if "feature_metadata" in list(genparams.keys()):
mp.add_feature_metadata(genparams["feature_metadata"])
tb.set_metagenomic_profile(mp)
# work around for plug-in issues
if "area_plot" in tb.params:
run_order.insert(0, tb)
else:
run_order.append(tb)
# Copy parameters file to new directory.
shutil.copyfile(filename, output_dir + "/" + filename)
os.chdir(output_dir)
# Call run on each test.
for tb in run_order:
result = tb.run()
test_results[tb] = result
try:
if genparams["to_html"][0] == "t":
results_web_page = generate_html.create_page(test_results, output_dir, filename, order=tests)
try:
if genparams["open_page"][0] == "t":
webbrowser.open(results_web_page)
except IndexError:
print("Warning: HTML page could not be opened. Value for 'open_page' missing in parameters file.")
except IndexError:
print("Warning: HTML page could not be created. Value for 'to_html' missing in parameters file.")
# Done
print("Tests complete.")
print(("Output saved at " + genparams["output_directory"]))