def compute_stratified_mean_enrichments(self,
min_means=[0.1],
num_around=100,
exclude_from_edges=[(90, 90),
(200, 200),
(200, 0),
(300, 0),
(0, 0),
],
do_anisomycin=False,
do_stringent=False,
):
specific_keys = {'relaxed', 'identities'}
if do_anisomycin:
specific_keys.add('anisomycin')
if do_stringent:
specific_keys.add('stringent')
codon_counts = self.read_file('buffered_codon_counts',
specific_keys=specific_keys,
)
enrichments = pausing.fast_stratified_mean_enrichments(codon_counts,
exclude_from_edges,
min_means,
num_around,
count_type='relaxed',
)
self.write_file('stratified_mean_enrichments', enrichments)
if do_stringent:
enrichments = pausing.fast_stratified_mean_enrichments(codon_counts,
exclude_from_edges,
min_means,
num_around,
count_type='stringent',
)
self.write_file('stratified_mean_enrichments_stringent', enrichments)
if do_anisomycin:
enrichments = pausing.fast_stratified_mean_enrichments(codon_counts,
exclude_from_edges,
min_means,
num_around,
count_type='anisomycin',
)
self.write_file('stratified_mean_enrichments_anisomycin', enrichments)
def compute_stratified_mean_enrichments(self, min_means=[0.1, 0]):
''' Ugly duplication of code in ribosome_profiling_experiment '''
num_before = 90
num_after = 90
def find_breakpoints(sorted_names, means, min_means):
breakpoints = {}
zipped = zip(sorted_names, means)
for min_mean in min_means:
name = [name for name, mean in zipped if mean > min_mean][-1]
breakpoints[name] = '{0:0.2f}'.format(min_mean)
return breakpoints
codon_counts = self.read_file('simulated_codon_counts',
specific_keys={'relaxed', 'identities'},
)
sorted_names, means = pausing.order_by_mean_density(codon_counts,
count_type='relaxed',
num_before=num_before,
num_after=num_after,
)
breakpoints = find_breakpoints(sorted_names, means, min_means)
enrichments = pausing.fast_stratified_mean_enrichments(codon_counts,
sorted_names,
breakpoints,
num_before,
num_after,
count_type='relaxed',
)
self.write_file('stratified_mean_enrichments', enrichments)