def _apply_mask(self, gtdb_msa, user_msa, msa_mask, min_perc_aa):
"""Apply canonical mask to MSA file."""
aligned_genomes = merge_two_dicts(gtdb_msa, user_msa)
list_mask = np.fromfile(msa_mask, dtype='S1') == b'1'
output_seqs = {}
pruned_seqs = {}
bar_fmt = '==> Masked {n_fmt}/{total_fmt} ({percentage:.0f}%) ' \
'alignments [{rate_fmt}, ETA {remaining}]'
for seq_id, seq in tqdm(aligned_genomes.items(), bar_format=bar_fmt):
list_seq = np.fromiter(seq, dtype='S1')
if list_mask.shape[0] != list_seq.shape[0]:
raise MSAMaskLengthMismatch(
'Mask and alignment length do not match.')
list_masked_seq = list_seq[list_mask]
masked_seq_unique = np.unique(list_masked_seq, return_counts=True)
masked_seq_counts = defaultdict(lambda: 0)
for aa_char, aa_count in zip(masked_seq_unique[0],
masked_seq_unique[1]):
masked_seq_counts[aa_char.decode('utf-8')] = aa_count
masked_seq = list_masked_seq.tostring().decode('utf-8')
valid_bases = list_masked_seq.shape[0] - masked_seq_counts[
'.'] - masked_seq_counts['-']
if seq_id in user_msa and valid_bases < list_masked_seq.shape[
0] * min_perc_aa:
pruned_seqs[seq_id] = masked_seq
continue
output_seqs[seq_id] = masked_seq
return output_seqs, pruned_seqs
def _apply_mask(self, gtdb_msa, user_msa, msa_mask, min_perc_aa):
"""Apply canonical mask to MSA file."""
aligned_genomes = merge_two_dicts(gtdb_msa, user_msa)
list_mask = np.fromfile(msa_mask, dtype='S1') == b'1'
output_seqs, pruned_seqs = dict(), dict()
for seq_id, seq in tqdm_log(aligned_genomes.items(), unit='sequence'):
list_seq = np.fromiter(seq, dtype='S1')
if list_mask.shape[0] != list_seq.shape[0]:
raise MSAMaskLengthMismatch(
f'Mask ({list_mask.shape[0]}) and alignment ({list_seq.shape[0]}) length do not match.'
)
list_masked_seq = list_seq[list_mask]
masked_seq_unique = np.unique(list_masked_seq, return_counts=True)
masked_seq_counts = defaultdict(lambda: 0)
for aa_char, aa_count in zip(masked_seq_unique[0],
masked_seq_unique[1]):
masked_seq_counts[aa_char.decode('utf-8')] = aa_count
masked_seq = list_masked_seq.tostring().decode('utf-8')
valid_bases = list_masked_seq.shape[0] - \
masked_seq_counts['.'] - masked_seq_counts['-']
if seq_id in user_msa and valid_bases < list_masked_seq.shape[
0] * min_perc_aa:
pruned_seqs[seq_id] = masked_seq
continue
output_seqs[seq_id] = masked_seq
return output_seqs, pruned_seqs
def _apply_mask(self, gtdb_msa, user_msa, msa_mask, min_perc_aa):
"""Apply canonical mask to MSA file."""
aligned_genomes = merge_two_dicts(gtdb_msa, user_msa)
with open(msa_mask, 'r') as f:
mask = f.readline().strip()
list_mask = np.array([True if c == '1' else False for c in mask],
dtype=bool)
output_seqs = {}
pruned_seqs = {}
for seq_id, seq in aligned_genomes.iteritems():
if len(mask) != len(seq):
self.logger.error('Mask and alignment length do not match.')
raise MSAMaskLengthMismatch(
'Mask and alignment length do not match.')
masked_seq = ''.join(np.array(list(seq), dtype=str)[list_mask])
valid_bases = len(masked_seq) - masked_seq.count(
'.') - masked_seq.count('-')
if seq_id in user_msa and valid_bases < len(
masked_seq) * min_perc_aa:
pruned_seqs[seq_id] = masked_seq
continue
output_seqs[seq_id] = masked_seq
return output_seqs, pruned_seqs