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Update vcf file processing #124

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Update vcf file processing #124

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21ac8a8
Load dosage such that 2=HOM_ALT instead of 2=UNKNOWN
jelman Apr 29, 2021
969ec55
alts loaded as list, check length of first element
jelman Apr 29, 2021
d2ad59f
Check for multiples in REFs and ALTs
jelman Apr 29, 2021
a88810b
logging.log() requires integer level
jelman Apr 29, 2021
bb678f3
Use numpy.nanmean to allow for nans
jelman Apr 29, 2021
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10 changes: 5 additions & 5 deletions software/metax/genotype/CYVCF2Genotype.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@

def vcf_file_geno_lines(path, mode="genotyped", variant_mapping=None, whitelist=None, skip_palindromic=False, liftover_conversion=None):
logging.log(9, "Processing vcf %s", path)
vcf_reader = VCF(path)
vcf_reader = VCF(path, gts012=True)
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@Fnyasimi Fnyasimi Feb 7, 2022

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What does gts012 represent?

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@jelman jelman Feb 7, 2022

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From cyvcf2.VCF documentation:
gts012 (bool) – if True, then gt_types will be 0=HOM_REF, 1=HET, 2=HOM_ALT, 3=UNKNOWN. If False, 3, 2 are flipped.


is_dict_mapping = variant_mapping is not None and type(variant_mapping) == dict

Expand Down Expand Up @@ -40,12 +40,12 @@ def vcf_file_geno_lines(path, mode="genotyped", variant_mapping=None, whitelist=
for sample in variant.genotypes:
d_ = (sample[0] == a+1) + (sample[1] == a+1)
d.append(d_)
f = numpy.mean(numpy.array(d,dtype=numpy.int32))/2
f = numpy.nanmean(numpy.array(d,dtype=numpy.int32))/2
yield (variant_id, chr, pos, ref, alt, f) + tuple(d)

elif mode == "imputed":
if len(alts) > 1:
logging.log("VCF imputed mode doesn't support multiple ALTs, skipping %s", variant_id)
if (len(ref)) | (len(alts[0])) > 1:
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@Fnyasimi Fnyasimi Feb 7, 2022

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The genotype contains indels too?

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@jelman jelman Feb 7, 2022

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Yes, and they could be coded as either REF or ALT.

logging.log(8, "VCF imputed mode doesn't support multiple REFs or ALTs, skipping %s", variant_id)
continue

alt = alts[0]
Expand All @@ -60,7 +60,7 @@ def vcf_file_geno_lines(path, mode="genotyped", variant_mapping=None, whitelist=

try:
d = numpy.apply_along_axis(lambda x: x[0], 1, variant.format("DS"))
f = numpy.mean(numpy.array(d)) / 2
f = numpy.nanmean(numpy.array(d)) / 2
yield (variant_id, chr, pos, ref, alt, f) + tuple(d)
except KeyError:
yield RuntimeError("Missing DS field when vcf mode is imputed")
Expand Down