def plot_minor_allele_frequency_filtered(data_folder, adaID, fragments, VERBOSE=0,
savefig=False):
'''Plot minor allele frequency along the genome'''
nus = np.load(get_merged_allele_frequencies_filename(data_folder, adaID, fragments))
nu_min = np.ma.masked_all(nus.shape[-1])
for pos, nutmp in enumerate(nus.T):
try:
if not np.ma.is_masked(nutmp):
nu_min[pos] = np.sort(nutmp)[-2]
except ValueError:
print pos, np.ma.is_masked(nutmp)
import ipdb; ipdb.set_trace()
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1, figsize=(15, 8))
ax.plot(nu_min, lw=1.5, c='k')
ax.scatter(np.arange(len(nu_min)), nu_min, s=30, c='k')
ax.set_yscale('log')
ax.set_xlabel('Position')
ax.set_ylabel(r'$\nu$', fontsize=20)
ax.set_title('adaID '+adaID+', '+'-'.join(fragments))
ax.set_xlim(-100, len(nu_min) + 100)
plt.tight_layout()
if savefig:
from hivwholeseq.sequencing.filenames import \
get_minor_allele_frequency_merged_figure_filename as gff
outputfile = gff(data_folder, adaID, fragments)
fig.savefig(outputfile)
plt.close(fig)
else:
plt.ion()
plt.show()
def plot_minor_allele_frequency_filtered(data_folder,
adaID,
fragments,
VERBOSE=0,
savefig=False):
'''Plot minor allele frequency along the genome'''
nus = np.load(
get_merged_allele_frequencies_filename(data_folder, adaID, fragments))
nu_min = np.ma.masked_all(nus.shape[-1])
for pos, nutmp in enumerate(nus.T):
try:
if not np.ma.is_masked(nutmp):
nu_min[pos] = np.sort(nutmp)[-2]
except ValueError:
print pos, np.ma.is_masked(nutmp)
import ipdb
ipdb.set_trace()
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1, figsize=(15, 8))
ax.plot(nu_min, lw=1.5, c='k')
ax.scatter(np.arange(len(nu_min)), nu_min, s=30, c='k')
ax.set_yscale('log')
ax.set_xlabel('Position')
ax.set_ylabel(r'$\nu$', fontsize=20)
ax.set_title('adaID ' + adaID + ', ' + '-'.join(fragments))
ax.set_xlim(-100, len(nu_min) + 100)
plt.tight_layout()
if savefig:
from hivwholeseq.sequencing.filenames import \
get_minor_allele_frequency_merged_figure_filename as gff
outputfile = gff(data_folder, adaID, fragments)
fig.savefig(outputfile)
plt.close(fig)
else:
plt.ion()
plt.show()
samples = dataset.samples
if adaIDs is not None:
samples = samples.loc[samples.adapter.isin(adaIDs)]
if VERBOSE >= 3:
print 'adaIDs', samples.adapter
for samplename, sample in samples.iterrows():
sample = SampleSeq(sample)
adaID = sample.adapter
if VERBOSE >= 1:
print adaID, samplename
fragments = [fr[:2] for fr in sample.regions_complete]
if (len(fragments) != 6) and (VERBOSE >= 1):
print 'WARNING: only '+str(len(fragments))+' regions found!'
# Write one or more merged consensi
consensus = merge_consensi(data_folder, adaID, fragments, VERBOSE=VERBOSE)
for (frags, cons) in consensus:
output_filename = get_merged_consensus_filename(data_folder, adaID, frags)
SeqIO.write(cons, output_filename, 'fasta')
# Write allele frequencies
if do_nus:
nu = merge_allele_frequencies(data_folder, adaID, fragments, VERBOSE=VERBOSE)
for (frags, nuf) in nu:
output_filename = get_merged_allele_frequencies_filename(data_folder, adaID, frags)
nuf.dump(output_filename)
