def find_match(self, df):
"""Find a taxId that best describes top hits.
Parameters
----------
df : pd.DataFrame
hit table
Returns
-------
str
taxId of match, or '0' if not found
Notes
-----
The best match TaxID is the LCA of top hits. The "top hits" are
defined as those whose bit scores are no less than a certain
percentage of that of the best hit. This behavior is similar to
DIAMOND's taxonomic classification function.
"""
try:
th = df.iloc[0]['score'] * self.match_th
except IndexError:
return '0'
return find_lca(df[df['score'] >= th]['taxid'], self.taxdump)
def infer_close_group(self):
"""Infer close group automatically.
Notes
-----
1. Assign `close_tax` as top-level taxId(s) of the close group.
2. Assign `groups['close']` as all taxIds under the close group.
"""
mems = []
# start from the LCA of self group
cid = find_lca(self.self_tax, self.taxdump)
while True:
# close group should exclude self group
mems = set([cid] + get_descendants(cid, self.taxdump)).difference(
self.groups['self'])
# stop when size limit is reached
if mems and (not self.close_size or len(mems) >= self.close_size):
break
# move up one level
pid = self.taxdump[cid]['parent']
if pid == cid or pid == '0':
break
cid = pid
self.close_tax = [cid]
self.groups['close'] = mems
def assign_taxonomy(self):
"""Assign taxonomy to genomes.
"""
# take user-defined taxIds of input genomes
if self.input_tax:
try:
self.input_tax = dict_from_param(self.input_tax)
except ValueError:
if len(self.data) > 1:
raise ValueError('Invalid input taxonomy format.')
# for single-sample analysis, one can simply enter a taxId
self.input_tax = {max(self.data.keys()): self.input_tax}
print('User-specified TaxIDs of input genomes:')
for sid, tid in sorted(self.input_tax.items()):
if tid not in self.taxdump:
# TODO: read from both temp and master taxdump
raise ValueError('TaxID {} is not present in taxonomy '
'database.'.format(tid))
print(' {}: {} ({}).'.format(sid, tid,
self.taxdump[tid]['name']))
else:
self.input_tax = {}
# auto-infer taxIds of remaining genomes
sids = sorted([x for x in self.data if x not in self.input_tax])
if sids:
print('Auto-inferring plausible taxIds for input genomes based on '
'taxonomy of search results...')
for sid in sids:
try:
tid, cov = self.infer_genome_tax(self.data[sid],
self.taxdump,
self.input_cov)
self.input_tax[sid] = tid
except ValueError:
raise ValueError('Cannot auto-infer taxonomy for {}. '
'Please specify manually.'.format(sid))
print(' {}: {} ({}) (covering {:2g}% best hits).'.format(
sid, tid, self.taxdump[tid]['name'], cov))
# refine taxonomy database
print('Refining taxonomy database...')
refine_taxdump(self.sum_taxids(), self.taxdump)
add_children(self.taxdump)
print('Done. Retained {} taxa.'.format(len(self.taxdump)))
# find lowest common ancestor (LCA) of all genomes
self.lca = find_lca(self.input_tax.values(), self.taxdump)
print('All input genomes belong to {} ({}).'.format(
self.lca, describe_taxon(self.lca, self.taxdump)))
def build_taxonmap(self):
"""Build protein-to-taxonomy map.
"""
# assign shared protein to lowest common ancestor (LCA)
self.taxonmap = {
p: max(tids) if len(tids) == 1 else find_lca(tids, self.taxdump)
for p, tids in self.p2tids.items()
}
# write taxonomy map
fname = 'taxon.map.gz'
with gzip.open(join(self.output, fname), 'wb') as f:
for p, tid in sorted(self.taxonmap.items()):
f.write(f'{p}\t{tid}\n'.encode())
print(f'Protein-to-taxonomy map written to {fname}.')
def test_find_lca(self):
taxdump = taxdump_from_text(taxdump_archaea)
self.assertEqual(find_lca(['131567'], taxdump), '131567')
self.assertEqual(find_lca(['1935183', '1783276'], taxdump), '2157')
self.assertEqual(find_lca(['1935183', '1783276', '1655434'], taxdump),
'2157')
self.assertEqual(find_lca(['1935183', '1783276', '2157'], taxdump),
'2157')
self.assertEqual(find_lca(['1935183', '2'], taxdump), '131567')
self.assertEqual(find_lca(['1', '2', '1'], taxdump), '1')
taxdump['x'] = {'name': 'x', 'parent': 'x'}
with self.assertRaises(ValueError) as ctx:
find_lca(['2', 'x'], taxdump)
msg = 'Cannot find LCA of taxIds in database.'
self.assertEqual(str(ctx.exception), msg)
