Pandas ExtensionDtypes and ExtensionArray for working with genomics data
Variant objects holds information about a particular variant:
from pandas_genomics.scalars import Variant
variant = Variant('12', 112161652, id='rs12462', ref='A', alt=['C', 'T'])
print(variant)rs12462[chr=12;pos=112161652;ref=A;alt=C,T]
Genotype objects are associated with a particular Variant:
gt = variant.make_genotype("A", "C")
print(gt)A/C
The GenotypeArray stores genotypes with an associated variant and has useful methods and properties:
from pandas_genomics.scalars import Variant
from pandas_genomics.arrays import GenotypeArray
variant = Variant('12', 112161652, id='rs12462', ref='A', alt=['C'])
gt_array = GenotypeArray([variant.make_genotype_from_str(s) for s in ["C/C", "A/C", "A/A"]])
print(gt_array)<GenotypeArray>
[Genotype(variant=rs12462[chr=12;pos=112161652;ref=A;alt=C], allele1=1, allele2=1),
Genotype(variant=rs12462[chr=12;pos=112161652;ref=A;alt=C], allele1=0, allele2=1),
Genotype(variant=rs12462[chr=12;pos=112161652;ref=A;alt=C], allele1=0, allele2=0)]
Length: 3, dtype: genotype[12; 112161652; rs12462; A; C]
print(gt_array.astype(str)) ['C/C' 'A/C' 'A/A']
print(gt_array.encode_dominant()) <IntegerArray>
[1, 1, 0]
Length: 3, dtype: UInt8
There are also genomics accessors for Series and DataFrame
import pandas as pd
print(pd.Series(gt_array).genomics.encode_codominant()) 0 Hom
1 Het
2 Ref
Name: rs12462_C, dtype: category
Categories (3, object): ['Ref' < 'Het' < 'Hom']
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