def test_get_genes(cyvcf2_variant):
csq_entry = "C|missense_variant|MODERATE|POC1A|ENSG00000164087|"\
"Transcript|ENST00000296484|protein_coding|4/11||ENST00000296484.2"\
":c.322A>G|ENSP00000296484.2:p.Ser108Gly|362|322|108|S/G|Agt/Ggt"\
"|||-1|HGNC|24488||CCDS2846.1|ENSP00000296484|POC1A_HUMAN|"\
"B2RDV4_HUMAN|UPI000045711C|deleterious|possibly_damaging|"\
"PROSITE_profiles:PS50082&PROSITE_profiles:PS50294&hmmpanther"\
":PTHR22847:SF319&hmmpanther:PTHR22847&Gene3D:2.130.10.10&"\
"Pfam_domain:PF00400&SMART_domains:SM00320&Superfamily_domains:"\
"SSF50978|||||,C|missense_variant|MODERATE|POC1A|ENSG00000164087"\
"|Transcript|ENST00000394970|protein_coding|4/10||"\
"ENST00000394970.2:c.322A>G|ENSP00000378421.2:p.Ser108Gly|640"\
"|322|108|S/G|Agt/Ggt|||-1|HGNC|24488||CCDS54592.1|ENSP00000378421"\
"|POC1A_HUMAN||UPI00006633C6|deleterious|benign|"\
"Superfamily_domains:SSF50978&SMART_domains:SM00320&Pfam_domain"\
":PF00400&Gene3D:2.130.10.10&hmmpanther:PTHR22847&hmmpanther:"\
"PTHR22847:SF319&PROSITE_profiles:PS50082&PROSITE_profiles:PS50294"\
"|||||,C|missense_variant|MODERATE|POC1A|ENSG00000164087|"\
"Transcript|ENST00000474012|protein_coding|4/11||ENST00000474012"\
".1:c.208A>G|ENSP00000418968.1:p.Ser70Gly|425|208|70|S/G|Agt"\
"/Ggt|||-1|HGNC|24488||CCDS54591.1|ENSP00000418968|POC1A_HUMAN|"\
"B2RDV4_HUMAN|UPI0000E1FCF5|tolerated|possibly_damaging|Superfami"\
"ly_domains:SSF50978&SMART_domains:SM00320&Gene3D:2.130.10.10&"\
"Pfam_domain:PF00400&hmmpanther:PTHR22847:SF319&hmmpanther:"\
"PTHR22847&PROSITE_profiles:PS50294&PROSITE_profiles:PS50082|||||"
csq_header = "Allele|Consequence|IMPACT|SYMBOL|Gene|Feature_type|"\
"Feature|BIOTYPE|EXON|INTRON|HGVSc|HGVSp|cDNA_position|CDS_position|"\
"Protein_position|Amino_acids|Codons|Existing_variation|DISTANCE|"\
"STRAND|SYMBOL_SOURCE|HGNC_ID|TSL|CCDS|ENSP|SWISSPROT|TREMBL|UNIPARC|"\
"SIFT|PolyPhen|DOMAINS|HGVS_OFFSET|MOTIF_NAME|MOTIF_POS|HIGH_INF_POS|"\
"MOTIF_SCORE_CHANGE"
header = [word.upper() for word in csq_header.split('|')]
## GIVEN a variant with vep annotation and a vep header
raw_transcripts = (
dict(
zip(
header,
csq_entry.split('|')
)
)
for transcript_info in csq_entry.split(',')
)
parsed_transcripts = []
for parsed_transcript in parse_transcripts(raw_transcripts, allele='C'):
parsed_transcripts.append(parsed_transcript)
# variant = cyvcf2_variant
# variant.INFO['CSQ'] = csq_entry
genes = parse_genes(parsed_transcripts)
for gene in genes:
assert gene['hgnc_id'] == 24488
assert len(genes) == 1
def test_get_genes(cyvcf2_variant):
csq_entry = (
"C|missense_variant|MODERATE|POC1A|ENSG00000164087|"
"Transcript|ENST00000296484|protein_coding|4/11||ENST00000296484.2"
":c.322A>G|ENSP00000296484.2:p.Ser108Gly|362|322|108|S/G|Agt/Ggt"
"|||-1|HGNC|24488||CCDS2846.1|ENSP00000296484|POC1A_HUMAN|"
"B2RDV4_HUMAN|UPI000045711C|deleterious|possibly_damaging|"
"PROSITE_profiles:PS50082&PROSITE_profiles:PS50294&hmmpanther"
":PTHR22847:SF319&hmmpanther:PTHR22847&Gene3D:2.130.10.10&"
"Pfam_domain:PF00400&SMART_domains:SM00320&Superfamily_domains:"
"SSF50978|||||,C|missense_variant|MODERATE|POC1A|ENSG00000164087"
"|Transcript|ENST00000394970|protein_coding|4/10||"
"ENST00000394970.2:c.322A>G|ENSP00000378421.2:p.Ser108Gly|640"
"|322|108|S/G|Agt/Ggt|||-1|HGNC|24488||CCDS54592.1|ENSP00000378421"
"|POC1A_HUMAN||UPI00006633C6|deleterious|benign|"
"Superfamily_domains:SSF50978&SMART_domains:SM00320&Pfam_domain"
":PF00400&Gene3D:2.130.10.10&hmmpanther:PTHR22847&hmmpanther:"
"PTHR22847:SF319&PROSITE_profiles:PS50082&PROSITE_profiles:PS50294"
"|||||,C|missense_variant|MODERATE|POC1A|ENSG00000164087|"
"Transcript|ENST00000474012|protein_coding|4/11||ENST00000474012"
".1:c.208A>G|ENSP00000418968.1:p.Ser70Gly|425|208|70|S/G|Agt"
"/Ggt|||-1|HGNC|24488||CCDS54591.1|ENSP00000418968|POC1A_HUMAN|"
"B2RDV4_HUMAN|UPI0000E1FCF5|tolerated|possibly_damaging|Superfami"
"ly_domains:SSF50978&SMART_domains:SM00320&Gene3D:2.130.10.10&"
"Pfam_domain:PF00400&hmmpanther:PTHR22847:SF319&hmmpanther:"
"PTHR22847&PROSITE_profiles:PS50294&PROSITE_profiles:PS50082|||||"
)
csq_header = (
"Allele|Consequence|IMPACT|SYMBOL|Gene|Feature_type|"
"Feature|BIOTYPE|EXON|INTRON|HGVSc|HGVSp|cDNA_position|CDS_position|"
"Protein_position|Amino_acids|Codons|Existing_variation|DISTANCE|"
"STRAND|SYMBOL_SOURCE|HGNC_ID|TSL|CCDS|ENSP|SWISSPROT|TREMBL|UNIPARC|"
"SIFT|PolyPhen|DOMAINS|HGVS_OFFSET|MOTIF_NAME|MOTIF_POS|HIGH_INF_POS|"
"MOTIF_SCORE_CHANGE"
)
header = [word.upper() for word in csq_header.split("|")]
## GIVEN a variant with vep annotation and a vep header
raw_transcripts = (
dict(zip(header, csq_entry.split("|")))
for transcript_info in csq_entry.split(",")
)
parsed_transcripts = []
for parsed_transcript in parse_transcripts(raw_transcripts, allele="C"):
parsed_transcripts.append(parsed_transcript)
# variant = cyvcf2_variant
# variant.INFO['CSQ'] = csq_entry
genes = parse_genes(parsed_transcripts)
for gene in genes:
assert gene["hgnc_id"] == 24488
assert len(genes) == 1
def test_parse_functional_annotation(vep_csq_header, vep_csq):
"""Test parsing functional annotation"""
## GIVEN a transcript with the functional annotation in the CSQ
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript["functional_annotations"] == ["synonymous_variant"]
def test_parse_functional_annotation():
csq_header = "Allele|Consequence"
csq_entry = "C|missense_variant"
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [dict(zip(header, entry.split('|'))) for entry in csq_entry.split(',')]
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript['functional_annotations'] == ['missense_variant']
def test_parse_functional_annotation():
csq_header = "Allele|Consequence"
csq_entry = "C|missense_variant"
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript["functional_annotations"] == ["missense_variant"]
def test_parse_functional_annotation():
csq_header = "Allele|Consequence"
csq_entry = "C|missense_variant"
raw_transcripts = [
dict(zip(csq_header.split('|'), entry.split('|')))
for entry in csq_entry.split(',')
]
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript['functional_annotations'] == ['missense_variant']
def test_parse_optional_hgnc_annotation(vep_csq_header, vep_csq):
"""Test parsing the HGNC id from the CSQ field"""
## GIVEN a transcript with the optional hgnc annotation
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correctly
for transcript in transcripts:
assert transcript["functional_annotations"] == ["synonymous_variant"]
assert transcript["hgnc_id"] == 10593
def test_parse_regular_hgnc_annotation():
csq_header = "Allele|Consequence|HGNC_ID"
csq_entry = "C|missense_variant|10001"
raw_transcripts = [
dict(zip(csq_header.split('|'), entry.split('|')))
for entry in csq_entry.split(',')
]
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript['functional_annotations'] == ['missense_variant']
assert transcript['hgnc_id'] == 10001
def test_parse_hg38_mane_transcripts(vep_csq_header, vep_csq):
"""Testing MANE trascripts parsing for genome build 38"""
# GIVEN a transcript with the MANE trancript value in th CSQ
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the MANE annotation is parsed correctly
for transcript in transcripts:
assert transcript["mane_select_transcript"] == "NM_000335.5"
assert transcript["mane_plus_clinical_transcript"] == "NM_001099404.2"
def test_parse_hg38_mane_transcripts():
"""Testing MANE trascripts parsing for genome build 38"""
# GIVEN a transcript with the MANE trancript value in th CSQ
header = [word.upper() for word in csq_build_38_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|")))
for entry in csq_build_38_entry.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the MANE annotation is parsed correctly
for transcript in transcripts:
assert transcript["mane_transcript"] == "NM_198576.4"
def test_parse_vep_freq_exac():
## GIVEN a transcript with the 1000G frequency
freq = 0.01
csq_header = "Allele|Consequence|EXAC_MAX_AF"
csq_entry = "C|missense_variant|{0}".format(freq)
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [dict(zip(header, entry.split('|')))
for entry in csq_entry.split(',')]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['exac_max'] == freq
def test_parse_vep_freq_thousand_g_alt(vep_csq_header, vep_csq):
"""Test extracting the 1000G allele frequency (AF) from the CSQ entry"""
## GIVEN a transcript with the 1000G frequency
freq = 0.9242
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the AF annotation is parsed correctly
for transcript in transcripts:
assert transcript["thousand_g_maf"] == freq
def test_parse_vep_freq_thousand_g_max():
## GIVEN a transcript with the 1000G frequency
freqs = [0.01, 0.001]
csq_header = "Allele|Consequence|AFR_AF|AMR_AF"
csq_entry = "C|missense_variant|{0}|{1}".format(freqs[0], freqs[1])
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [dict(zip(header, entry.split('|')))
for entry in csq_entry.split(',')]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['thousandg_max'] == max(freqs)
def test_parse_optional_hgnc_annotation():
## GIVEN a transcript with the optional hgnc annotation
csq_header = "Allele|Consequence|HGNC_ID"
csq_entry = "C|missense_variant|HGNC:10001"
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [dict(zip(header, entry.split('|'))) for entry in csq_entry.split(',')]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['functional_annotations'] == ['missense_variant']
assert transcript['hgnc_id'] == 10001
def test_parse_vep_freq_gnomad():
"""Test extracting the Gnomad AF from the CSQ field"""
## GIVEN a transcript with the gnomAD_AF
freq = 0.3428
header = [word.upper() for word in csq_build_38_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|")))
for entry in csq_build_38_entry.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the gnomAD_AF annotation is parsed correctly
for transcript in transcripts:
assert transcript["gnomad_maf"] == freq
def test_parse_transcripts(cyvcf2_variant):
## GIVEN some transcript information and a vep header
csq_entry = "C|missense_variant|MODERATE|POC1A|ENSG00000164087|"\
"Transcript|ENST00000296484|protein_coding|4/11||ENST00000296484.2"\
":c.322A>G|ENSP00000296484.2:p.Ser108Gly|362|322|108|S/G|Agt/Ggt"\
"|||-1|HGNC|24488||CCDS2846.1|ENSP00000296484|POC1A_HUMAN|"\
"B2RDV4_HUMAN|UPI000045711C|deleterious|possibly_damaging|"\
"PROSITE_profiles:PS50082&PROSITE_profiles:PS50294&hmmpanther"\
":PTHR22847:SF319&hmmpanther:PTHR22847&Gene3D:2.130.10.10&"\
"Pfam_domain:PF00400&SMART_domains:SM00320&Superfamily_domains:"\
"SSF50978|||||,C|missense_variant|MODERATE|POC1A|ENSG00000164087"\
"|Transcript|ENST00000394970|protein_coding|4/10||"\
"ENST00000394970.2:c.322A>G|ENSP00000378421.2:p.Ser108Gly|640"\
"|322|108|S/G|Agt/Ggt|||-1|HGNC|24488||CCDS54592.1|ENSP00000378421"\
"|POC1A_HUMAN||UPI00006633C6|deleterious|benign|"\
"Superfamily_domains:SSF50978&SMART_domains:SM00320&Pfam_domain"\
":PF00400&Gene3D:2.130.10.10&hmmpanther:PTHR22847&hmmpanther:"\
"PTHR22847:SF319&PROSITE_profiles:PS50082&PROSITE_profiles:PS50294"\
"|||||,C|missense_variant|MODERATE|POC1A|ENSG00000164087|"\
"Transcript|ENST00000474012|protein_coding|4/11||ENST00000474012"\
".1:c.208A>G|ENSP00000418968.1:p.Ser70Gly|425|208|70|S/G|Agt"\
"/Ggt|||-1|HGNC|24488||CCDS54591.1|ENSP00000418968|POC1A_HUMAN|"\
"B2RDV4_HUMAN|UPI0000E1FCF5|tolerated|possibly_damaging|Superfami"\
"ly_domains:SSF50978&SMART_domains:SM00320&Gene3D:2.130.10.10&"\
"Pfam_domain:PF00400&hmmpanther:PTHR22847:SF319&hmmpanther:"\
"PTHR22847&PROSITE_profiles:PS50294&PROSITE_profiles:PS50082|||||"
csq_header = "Allele|Consequence|IMPACT|SYMBOL|Gene|Feature_type|"\
"Feature|BIOTYPE|EXON|INTRON|HGVSc|HGVSp|cDNA_position|CDS_position|"\
"Protein_position|Amino_acids|Codons|Existing_variation|DISTANCE|"\
"STRAND|SYMBOL_SOURCE|HGNC_ID|TSL|CCDS|ENSP|SWISSPROT|TREMBL|UNIPARC|"\
"SIFT|PolyPhen|DOMAINS|HGVS_OFFSET|MOTIF_NAME|MOTIF_POS|HIGH_INF_POS|"\
"MOTIF_SCORE_CHANGE"
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [
dict(zip(header, entry.split('|'))) for entry in csq_entry.split(',')
]
## WHEN parsing the transcript
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
## THEN assert that some information was correct
if transcript['transcript_id'] == 'ENST00000296484':
assert transcript['sift_prediction'] == 'deleterious'
assert transcript['functional_annotations'] == ['missense_variant']
def test_parse_vep_freq_thousand_g_alt():
## GIVEN a transcript with the 1000G frequency
freq = 0.01
csq_header = "Allele|Consequence|AF"
csq_entry = "C|missense_variant|{0}".format(freq)
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript["thousand_g_maf"] == freq
def test_parse_vep_freq_thousand_g_max():
## GIVEN a transcript with the 1000G frequency
freqs = [0.01, 0.001]
csq_header = "Allele|Consequence|AFR_AF|AMR_AF"
csq_entry = "C|missense_variant|{0}|{1}".format(freqs[0], freqs[1])
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [
dict(zip(header, entry.split('|'))) for entry in csq_entry.split(',')
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['thousandg_max'] == max(freqs)
def test_parse_vep_freq_exac():
## GIVEN a transcript with the 1000G frequency
freq = 0.01
csq_header = "Allele|Consequence|EXAC_MAX_AF"
csq_entry = "C|missense_variant|{0}".format(freq)
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [
dict(zip(header, entry.split('|'))) for entry in csq_entry.split(',')
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['exac_max'] == freq
def test_parse_regular_hgnc_annotation():
## GIVEN a transcript with the regular hgnc annotation
csq_header = "Allele|Consequence|HGNC_ID"
csq_entry = "C|missense_variant|10001"
raw_transcripts = [
dict(zip(csq_header.split('|'), entry.split('|')))
for entry in csq_entry.split(',')
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['functional_annotations'] == ['missense_variant']
assert transcript['hgnc_id'] == 10001
def test_parse_vep_freq_gnomad():
## GIVEN a transcript with the 1000G frequency
freq = 0.01
csq_header = "Allele|Consequence|gnomAD_AF"
csq_entry = "C|missense_variant|{0}".format(freq)
raw_transcripts = [
dict(zip(csq_header.split('|'), entry.split('|')))
for entry in csq_entry.split(',')
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript['gnomad_maf'] == freq
def test_parse_cadd(vep_csq_header, vep_csq):
"""Testing parsing of CADD_PHRED score from VEP-annotated transcripts"""
# GIVEN a transcript with the CADD score in th CSQ
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
tx_cadd = float(raw_transcripts[0].get("CADD_PHRED"))
## WHEN parsing the transcripts
transcripts = list(parse_transcripts(raw_transcripts))
# CADD score should be parsed correctly
assert isinstance(transcripts[0]["cadd"], float)
assert transcripts[0]["cadd"] == tx_cadd
def test_parse_regular_hgnc_annotation():
## GIVEN a transcript with the regular hgnc annotation
csq_header = "Allele|Consequence|HGNC_ID"
csq_entry = "C|missense_variant|10001"
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript["functional_annotations"] == ["missense_variant"]
assert transcript["hgnc_id"] == 10001
def test_parse_vep_freq_gnomad(vep_csq_header, vep_csq):
"""Test extracting the gnomAD AF (gnomAD_AF) from the CSQ field"""
## GIVEN a transcript with the gnomAD_AF key/value
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
gnomad_maf = float(raw_transcripts[0]["GNOMAD_AF"])
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the gnomAD_AF annotation is parsed correctly
for transcript in transcripts:
assert transcript["gnomad_maf"] == gnomad_maf
assert transcript["gnomad_max"]
def test_parse_vep_freq_thousand_g_max():
"""Test parsing thousandg_max value from the CSQ field"""
## GIVEN a transcript with the 1000G AFR_AF and AMR_AF frequencies
freqs = [0.01, 0.001]
csq_header = "Allele|Consequence|AFR_AF|AMR_AF"
csq_entry = "C|missense_variant|{0}|{1}".format(freqs[0], freqs[1])
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the hgnc annotation is parsed correct
for transcript in transcripts:
assert transcript["thousandg_max"] == max(freqs)
def test_parse_superdups_fractmatch():
# GIVEN a transcript with the UCSC superdups fracMatch
fract_match = [0.992904, 0.98967]
csq_header = "Allele|Consequence|genomic_superdups_frac_match"
csq_entry = "C|missense_variant|{0}&{1}".format(fract_match[0],
fract_match[1])
header = [word.upper() for word in csq_header.split('|')]
raw_transcripts = [
dict(zip(header, entry.split('|'))) for entry in csq_entry.split(',')
]
assert raw_transcripts[0][
'GENOMIC_SUPERDUPS_FRAC_MATCH'] == '0.992904&0.98967'
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript['superdups_fracmatch'] == fract_match
def test_parse_vep_freq_mtgnomad(vep_csq_header, vep_csq):
"""Test extracting the mitochondrial gnomAD AF (gnomAD_mt_AF_hom/het) from the CSQ field"""
## GIVEN a transcript with the gnomAD_AF key/value
header = [word.upper() for word in vep_csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in vep_csq.split(",")
]
gnomad_mt_hom = float(raw_transcripts[0]["GNOMAD_MT_AF_HOM"])
gnomad_mt_het = float(raw_transcripts[0]["GNOMAD_MT_AF_HET"])
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
## THEN assert that the gnomAD_AF annotation is parsed correctly
for transcript in transcripts:
assert transcript["gnomad_mt_homoplasmic"] == gnomad_mt_hom
assert transcript["gnomad_mt_heteroplasmic"] == gnomad_mt_het
def test_parse_superdups_fractmatch():
"""Test extracting genomic_superdups_frac_match values from the CSQ field"""
# GIVEN a transcript with the UCSC superdups fracMatch
fract_match = [0.992904, 0.98967]
csq_header = "Allele|Consequence|genomic_superdups_frac_match"
csq_entry = "C|missense_variant|{0}&{1}".format(fract_match[0],
fract_match[1])
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
assert raw_transcripts[0][
"GENOMIC_SUPERDUPS_FRAC_MATCH"] == "0.992904&0.98967"
## WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
assert transcript["superdups_fracmatch"] == fract_match
def test_parse_cosmic_csq_cosmic():
"""Test parsing cosmic IDs from 'COSMIC' CSQ entry"""
cosmic_id = "COSV99072206"
# GIVEN a CSQ entry containing a specific 'COSMIC' key
csq_header = "Consequence|COSMIC|COSMIC_CDS|COSMIC_GENE|COSMIC_STRAND|COSMIC_CNT|COSMIC_AA"
csq_entry = "missense_variant|{0}|c.913T>G|POLQ||2|p.S305A".format(
cosmic_id)
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
# WHEN parsing the transcripts
transcripts = parse_transcripts(raw_transcripts)
# THEN the COSMIC annotation should be parsed correctly
for transcript in transcripts:
assert transcript["cosmic"] == [cosmic_id]
def test_parse_transcripts():
## GIVEN some transcript information and a vep header
csq_entry = "A|missense_variant|MODERATE|ABCC2|ENSG00000023839|Transcript|ENST00000370449|protein_coding|10/32||ENST00000370449.4:c.1249G>A|ENSP00000359478.4:p.Val417Ile|1362|1249|417|V/I|Gtt/Att|||1||HGNC|53|YES|||CCDS7484.1|ENSP00000359478|Q92887||UPI000013D6CA||Ensembl|G|G||tolerated|benign|PROSITE_profiles:PS50929&hmmpanther:PTHR24223&hmmpanther:PTHR24223:SF176&TIGRFAM_domain:TIGR00957&Pfam_domain:PF00664&Gene3D:2hydA01&Superfamily_domains:SSF90123||||||12.834|9.654|8.373|10.218|-7.208|1.111|-6.097|-6.097|-12.417|-1.215|-9.514|-13.633||||5.48|-10.3|0.54096|0.000000|-0.327000|0.0978|0.00|255992|Benign|255992|criteria_provided&_multiple_submitters&_no_conflicts|,A|missense_variant|MODERATE|ABCC2|1244|Transcript|NM_000392.3|protein_coding|10/32||NM_000392.3:c.1249G>A|NP_000383.1:p.Val417Ile|1388|1249|417|V/I|Gtt/Att|||1||EntrezGene|53|YES||||NP_000383.1|||||RefSeq|G|G||tolerated|benign|||||||12.834|9.654|8.373|10.218|-7.208|1.111|-6.097|-6.097|-12.417|-1.215|-9.514|-13.633||||5.48|-10.3|0.54096|0.000000|-0.327000|0.0978|0.00|255992|Benign|255992|criteria_provided&_multiple_submitters&_no_conflicts|,A|missense_variant|MODERATE|ABCC2|1244|Transcript|NM_000392.4|protein_coding|10/32||NM_000392.4:c.1249G>A|NP_000383.1:p.Val417Ile|1496|1249|417|V/I|Gtt/Att|||1||EntrezGene|53|YES||||NP_000383.1||||rseq_mrna_nonmatch&rseq_cds_mismatch|RefSeq|G|G|OK|tolerated|benign|||||||12.834|9.654|8.373|10.218|-7.208|1.111|-6.097|-6.097|-12.417|-1.215|-9.514|-13.633||||5.48|-10.3|0.54096|0.000000|-0.327000|0.0978|0.00|255992|Benign|255992|criteria_provided&_multiple_submitters&_no_conflicts|"
csq_header = "Allele|Consequence|IMPACT|SYMBOL|Gene|Feature_type|Feature|BIOTYPE|EXON|INTRON|HGVSc|HGVSp|cDNA_position|CDS_position|Protein_position|Amino_acids|Codons|Existing_variation|DISTANCE|STRAND|FLAGS|SYMBOL_SOURCE|HGNC_ID|CANONICAL|TSL|APPRIS|CCDS|ENSP|SWISSPROT|TREMBL|UNIPARC|REFSEQ_MATCH|SOURCE|GIVEN_REF|USED_REF|BAM_EDIT|SIFT|PolyPhen|DOMAINS|HGVS_OFFSET|MOTIF_NAME|MOTIF_POS|HIGH_INF_POS|MOTIF_SCORE_CHANGE|MES-NCSS_downstream_acceptor|MES-NCSS_downstream_donor|MES-NCSS_upstream_acceptor|MES-NCSS_upstream_donor|MES-SWA_acceptor_alt|MES-SWA_acceptor_diff|MES-SWA_acceptor_ref|MES-SWA_acceptor_ref_comp|MES-SWA_donor_alt|MES-SWA_donor_diff|MES-SWA_donor_ref|MES-SWA_donor_ref_comp|MaxEntScan_alt|MaxEntScan_diff|MaxEntScan_ref|GERP++_NR|GERP++_RS|REVEL_rankscore|phastCons100way_vertebrate|phyloP100way_vertebrate|LoFtool|ExACpLI|CLINVAR|CLINVAR_CLNSIG|CLINVAR_CLNVID|CLINVAR_CLNREVSTAT|genomic_superdups_frac_match"
header = [word.upper() for word in csq_header.split("|")]
raw_transcripts = [
dict(zip(header, entry.split("|"))) for entry in csq_entry.split(",")
]
assert len(raw_transcripts) == 3
## WHEN parsing the transcript
transcripts = parse_transcripts(raw_transcripts)
for transcript in transcripts:
## THEN assert that some information was correct
if transcript["transcript_id"] == "ENST00000370449":
assert transcript["sift_prediction"] == "tolerated"
assert transcript["functional_annotations"] == ["missense_variant"]
assert transcript["gerp"] == "-10.3"
assert transcript["phast"] == "0.000000"
assert transcript["phylop"] == "-0.327000"
assert transcript["revel"] == 0.54096
