def setUp(self):
self.simple = Transcript("")
self.simple_new = Transcript("")
self.w_gid = Transcript("", gene_id="123")
self.w_tid = Transcript("", transcript_id="tid")
self.w_id = Transcript("", "gid", "tid")
#Internal indexing starts at 0! MutationSyntax coming e.g. from ANNOVAR starts at 1!
self.gcg_v1 = Variant(
"rs5650", VariationType.SNP, 2, 162145588, 'G', 'T', {
"NM_002054.4":
MutationSyntax("NM_002054.4", 343, 114, "c.344C>A", "p.A115D")
}, False, False)
self.gcg_ts = "gcatagaatgcagatgagcaaagtgagtgggagagggaagtcatttgtaacaaaaactcattatttacagatgagaaatttatattgtcagcgtaatatctgtgaggctaaacagagctggagagtatataaaagcagtgcgccttggtgcagaagtacagagcttaggacacagagcacatcaaaagttcccaaagagggcttgctctctcttcacctgctctgttctacagcacactaccagaagacagcagaaatgaaaagcatttactttgtggctggattatttgtaatgctggtacaaggcagctggcaacgttcccttcaagacacagaggagaaatccagatcattctcagcttcccaggcagacccactcagtgatcctgatcagatgaacgaggacaagcgccattcacagggcacattcaccagtgactacagcaagtatctggactccaggcgtgcccaagattttgtgcagtggttgatgaataccaagaggaacaggaataacattgccaaacgtcacgatgaatttgagagacatgctgaagggacctttaccagtgatgtaagttcttatttggaaggccaagctgccaaggaattcattgcttggctggtgaaaggccgaggaaggcgagatttcccagaagaggtcgccattgttgaagaacttggccgcagacatgctgatggttctttctctgatgagatgaacaccattcttgataatcttgccgccagggactttataaactggttgattcagaccaaaatcactgacaggaaataactatatcactattcaagatcatcttcacaacatcacctgctagccacgtgggatgtttgaaatgttaagtcctgtaaatttaagaggtgtattctgaggccacattgctttgcatgccaataaataaattttcttttagtgttgtgtagccaaaaattacaaatggaataaagttttatcaaaatattgctaaaatatcagctttaaaatatgaaagtgctagattctgttattttcttcttattttggatgaagtaccccaacctgtttacatttagcgataaaattatttttctatgatataatttgtaaatgtaaattattccgatctgacatatctgcattataataataggagaatagaagaactggtagccacagtggtgaaattggaaagagaactttcttcctgaaacctttgtcttaaaaatactcagctttcaatgtatcaaagatacaattaaataaaattttcaagcttctttaccattgtct"
self.w_v = Transcript(self.gcg_ts, 'GLUC_HUMAN', "NM_002054.4",
{343: self.gcg_v1})
def setUp(self):
self.simple = Peptide("SYFPEITHI")
self.gcg_ps = "MKSIYFVAGLFVMLVQGSWQRSLQDTEEKSRSFSASQADPLSDPDQMNEDKRHSQGTFTSDYSKYLDSRRAQDFVQWLMNTKRNRNNIAKRHDEFERHAEGTFTSDVSSYLEGQAAKEFIAWLVKGRGRRDFPEEVAIVEELGRRHADGSFSDEMNTILDNLAARDFINWLIQTKITDRK"
self.gcg_t1 = Transcript("", transcript_id="GLUC_HUMAN")
gcg_p1 = Protein(self.gcg_ps,
transcript_id='GLUC_HUMAN',
orig_transcript=self.gcg_t1)
self.w_p = Peptide("PROTEIN", {gcg_p1: [0]})
self.gcg_p1 = gcg_p1
self.gcg_v1 = Variant(
"rs5650", VariationType.SNP, 2, 162145588, 'G', 'T', {
"GLUC_HUMAN":
MutationSyntax("GLUC_HUMAN", 344, 115, "c.344C>A", "p.A115D")
}, False, False)
gcg_p1_copy = copy.deepcopy(gcg_p1)
gcg_p1_copy.vars = {0: [self.gcg_v1]}
self.w_v = Peptide("VARIANT", {gcg_p1_copy: [0]})
def read_variant_effect_predictor(file, gene_filter=None):
"""
Reads a VCF (v4.1) file generatede by variant effect predictor and generates variant objects
:param str file: Path to vcf file
:param list gene_filter: List of proteins (in HGNC) of inerrest. Variants are filter according to this list
:return: list(Variant) - a list of Fred2.Core.Variant objects
"""
vars = []
def get_type(ref, alt):
"""
returns the variant type
"""
if len(ref) == 1 and len(alt) == 1:
return VariationType.SNP
if len(ref) > 0 and len(alt) == 0:
if len(ref) % 3 == 0:
return VariationType.DEL
else:
return VariationType.FSDEL
if len(ref) == 0 and len(alt) > 0:
if len(alt) % 3 == 0:
return VariationType.INS
else:
return VariationType.FSINS
return VariationType.UNKNOWN
coding_types = set([
"3_prime_UTR_variant", "5_prime_UTR_variant", "start_lost",
"stop_gained", "frameshift_variant", "start_lost", "inframe_insertion",
"inframe_deletion", "missense_variant", "protein_altering_variant",
"splice_region_variant", "incomplete_terminal_codon_variant",
"stop_retained_variant", "synonymous_variant",
"coding_sequence_variant"
])
with open(file, "r") as f:
for i, l in enumerate(f):
#skip comments
if l.startswith("#") or l.strip() == "":
continue
chrom, gene_pos, var_id, ref, alt, _, filter_flag, info = l.strip(
).split("\t")[:8]
coding = {}
isSynonymous = False
for co in info.split(","):
#skip additional info fields without annotation
try:
#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|TSL|APPRIS|SIFT|PolyPhen|AF|AFR_AF|AMR_AF|EAS_AF|EUR_AF|SAS_AF|AA_AF|EA_AF|gnomAD_AF|gnomAD_AFR_AF|gnomAD_AMR_AF|gnomAD_ASJ_AF|gnomAD_EAS_AF|gnomAD_FIN_AF|gnomAD_NFE_AF|gnomAD_OTH_AF|gnomAD_SAS_AF|CLIN_SIG|SOMATIC|PHENO|PUBMED|MOTIF_NAME|MOTIF_POS|HIGH_INF_POS|MOTIF_SCORE_CHANGE">
_, var_type, _, gene, _, transcript_type, transcript_id, _, _, _, _, _, _, transcript_pos, prot_pos, aa_mutation = co.strip(
).split("|")[:16]
HGNC_ID = co.strip().split("|")[22]
except ValueError:
logging.warning(
"INFO field in different format in line: {}, skipping..."
.format(str(i)))
continue
#pass every other feature type except Transcript (RegulatoryFeature, MotifFeature.)
#pass genes that are uninterresting for us
if transcript_type != "Transcript" or (
HGNC_ID not in gene_filter and gene_filter):
continue
#pass all intronic and other mutations that do not directly influence the protein sequence
if any(t in coding_types for t in var_type.split("&")):
#generate mutation syntax
#positioning in Fred2 is 0-based!!!
if transcript_pos != "" and '?' not in transcript_pos:
coding[transcript_id] = MutationSyntax(
transcript_id,
int(transcript_pos.split("-")[0]) - 1,
-1 if prot_pos == "" else
int(prot_pos.split("-")[0]) - 1,
co,
"",
geneID=HGNC_ID)
#is variant synonymous?
isSynonymous = any(t == "synonymous_variant"
for t in var_type.split("&"))
if coding:
vars.append(
Variant(var_id, get_type(ref, alt), chrom, int(gene_pos),
ref.upper(), alt.upper(), coding, False,
isSynonymous))
return vars
def setUp(self):
self.simple = Variant(
"rs5650", VariationType.SNP, 2, 162145588, 'G', 'T', {
"NM_002054.4":
MutationSyntax("NM_002054.4", 344, 115, "c.344C>A", "p.A115D")
}, False, False)
def read_variant_effect_predictor(file, gene_filter=None):
"""
Reads a VCF (v4.1) file generatede by variant effect predictor and generates variant objects
:param str file: Path to vcf file
:param list gene_filter: List of proteins (in HGNC) of inerrest. Variants are filter according to this list
:return: list(Variant) - a list of Fred2.Core.Variant objects
"""
vars = []
def get_type(ref, alt):
"""
returns the variant type
"""
if len(ref)==1 and len(alt)==1:
return VariationType.SNP
if len(ref)>0 and len(alt)==0:
if len(ref)%3 == 0:
return VariationType.DEL
else:
return VariationType.FSDEL
if len(ref) == 0 and len(alt)>0:
if len(alt)% 3 == 0:
return VariationType.INS
else:
return VariationType.FSINS
return VariationType.UNKNOWN
coding_types = set(["3_prime_UTR_variant", "5_prime_UTR_variant", "start_lost", "stop_gained",
"frameshift_variant", "start_lost", "inframe_insertion", "inframe_deletion", "missense_variant",
"protein_altering_variant", "splice_region_variant", "incomplete_terminal_codon_variant", "stop_retained_variant",
"synonymous_variant", "coding_sequence_variant"])
with open(file, "r") as f:
for i,l in enumerate(f):
#skip comments
if l.startswith("#") or l.strip() == "":
continue
chrom, gene_pos,var_id,ref,alt,_,filter_flag,info= l.strip().split("\t")[:8]
coding = {}
isSynonymous = False
for co in info.split(","):
#Allele|Gene|Feature|Feature_type|Consequence|cDNA_position|CDS_position|Protein_position|Amino_acids|Codons|Existing_variation|DISTANCE|STRAND|SYMBOL|SYMBOL_SOURCE|HGNC_ID|CCDS">
_,gene,transcript_id,transcript_type,var_type,_,transcript_pos,prot_pos,_,_,_,distance,strand,HGNC_ID = co.strip().split("|")[:14]
#pass every other feature type except Transcript (RegulatoryFeature, MotifFeature.)
#pass genes that are uninterresting for us
if transcript_type != "Transcript" or (HGNC_ID not in gene_filter and gene_filter):
continue
#pass all intronic and other mutations that do not directly influence the protein sequence
if any(t in coding_types for t in var_type.split("&")):
#generate mutation syntax
#positioning in Fred2 is 0-based!!!
if transcript_pos != "":
coding[transcript_id] = MutationSyntax(transcript_id, int(transcript_pos.split("-")[0])-1,
-1 if prot_pos == "" else int(prot_pos.split("-")[0])-1, co, "", geneID=HGNC_ID)
#is variant synonymous?
isSynonymous = any(t == "synonymous_variant" for t in var_type.split("&"))
if coding:
vars.append(Variant(var_id, get_type(ref, alt), chrom, int(gene_pos), ref.upper(), alt.upper(), coding, False, isSynonymous))
return vars