def test_snv_consensus_case_2():
'''
test consensus.snv_consensus() with identical record between museq/samtools
Parameters
---------
Returns
-------
'''
chrom, pos, ref, alt, record = _get_test_record()
test_record = {(chrom, pos, ref, alt): record}
museq = test_record
freebayes = []
rtg = []
samtools = test_record
consensus_data = consensus.snv_consensus(museq, freebayes, rtg, samtools)
consensus_data = pd.DataFrame(consensus_data,
columns=["chrom", "pos", "ref", "alt", "id_counter", "qual", "filter", "nr", "na",
"nd"]
)
consensus_data = consensus_data.astype({"chrom": "str"})
_check_record([chrom, pos, ref, alt] + record, consensus_data)
def test_snv_consensus_case_9():
'''
test consensus.snv_consensus() with empty data
Parameters
---------
Returns
-------
'''
consensus_data = consensus.snv_consensus([], [], [], [])
assert consensus_data == []
def test_snv_consensus_case_8():
'''
test consensus.snv_consensus() with no identical records
Parameters
---------
Returns
-------
'''
chrom, pos, ref, alt, record = _get_test_record()
museq = {(chrom, pos + 1, ref, alt): record}
samtools = {(chrom, pos + 2, ref, alt): record}
freebayes = {(chrom, pos + 3, ref, alt): record}
rtg = {(chrom, pos + 4, ref, alt): record}
consensus_data = consensus.snv_consensus(museq, samtools, freebayes, rtg)
assert consensus_data == []
