def test_sum_taxids(self):
me = Analyze()
me.input_tax = {'S1': '1', 'S2': '3'}
def _hits_df(d):
return pd.Series(d, name='taxid').to_frame()
me.data = {
'S1': [{
'hits': _hits_df({
'a': '4',
'b': '6'
})
}, {
'hits': _hits_df({
'a': '4',
'c': '8'
})
}],
'S2': [{
'hits': _hits_df({
'b': '6',
'd': '1'
})
}]
}
obs = me.sum_taxids()
exp = {'1', '3', '4', '6', '8'}
self.assertSetEqual(obs, exp)
def test_assign_taxonomy(self):
# input are two genomes with defined taxonomy
me = Analyze()
me.input_tax = 'S1:561,S2:620' # Escherichia and Shigella
me.data = {}
me.taxdump = taxdump_from_text(taxdump_proteo)
me.assign_taxonomy()
# test input taxonomy extraction
self.assertDictEqual(me.input_tax, {'S1': '561', 'S2': '620'})
# test taxonomy refinement
exp = {
'1', '131567', '2', '1224', '1236', '91347', '543', '561', '620'
}
self.assertSetEqual(set(me.taxdump.keys()), exp)
# test LCA discovery
self.assertEqual(me.lca, '543')
# helper for making hit table
def _hits_df(d):
return pd.Series(d, name='taxid', dtype=object).to_frame()
# input is one genome with defined taxonomy
me = Analyze()
me.data = {'S1': [{'hits': pd.DataFrame(columns=['taxid'])}]}
me.input_tax = '561' # Escherichia
me.taxdump = taxdump_from_text(taxdump_proteo)
me.assign_taxonomy()
self.assertDictEqual(me.input_tax, {'S1': '561'})
# input taxonomy not found in database
me.input_tax = '1234'
me.taxdump = taxdump_from_text(taxdump_proteo)
with self.assertRaises(ValueError) as ctx:
me.assign_taxonomy()
msg = 'TaxID 1234 is not present in taxonomy database.'
self.assertEqual(str(ctx.exception), msg)
# input are two genome whose taxonomies are to be inferred based on
# search results
me = Analyze()
me.input_tax = None
me.data = {
'S1': [{
'hits': _hits_df({
'P1': '561',
'P2': '562'
})
}, {
'hits': _hits_df({
'P3': '543',
'P4': '561'
})
}],
'S2': [{
'hits': _hits_df({
'P5': '562',
'P6': '585056'
})
}, {
'hits': _hits_df({
'P7': '561',
'P8': '1038927'
})
}, {
'hits': _hits_df({'P9': '2580236'})
}]
}
me.input_cov = 75
me.taxdump = taxdump_from_text(taxdump_proteo)
me.assign_taxonomy()
self.assertDictEqual(me.input_tax, {'S1': '543', 'S2': '561'})
self.assertEqual(me.lca, '543')
# cannot auto-infer taxonomy
me.data['S3'] = [{'hits': _hits_df({})}]
me.taxdump = taxdump_from_text(taxdump_proteo)
with self.assertRaises(ValueError) as ctx:
me.assign_taxonomy()
msg = 'Cannot auto-infer taxonomy for S3. Please specify manually.'
self.assertEqual(str(ctx.exception), msg)
# invalid input taxonomy string
me.input_tax = '561'
with self.assertRaises(ValueError) as ctx:
me.assign_taxonomy()
msg = 'Invalid input taxonomy format.'
self.assertEqual(str(ctx.exception), msg)