def patterson_fst(aca, acb):
"""Estimator of differentiation between populations A and B based on the
F2 parameter.
Parameters
----------
aca : array_like, int, shape (n_variants, 2)
Allele counts for population A.
acb : array_like, int, shape (n_variants, 2)
Allele counts for population B.
Returns
-------
num : ndarray, shape (n_variants,), float
Numerator.
den : ndarray, shape (n_variants,), float
Denominator.
Notes
-----
See Patterson (2012), Appendix A.
TODO check if this is numerically equivalent to Hudson's estimator.
"""
from allel.stats.admixture import patterson_f2, h_hat
num = patterson_f2(aca, acb)
den = num + h_hat(aca) + h_hat(acb)
return num, den
def patterson_fst(aca, acb):
"""Estimator of differentiation between populations A and B based on the
F2 parameter.
Parameters
----------
aca : array_like, int, shape (n_variants, 2)
Allele counts for population A.
acb : array_like, int, shape (n_variants, 2)
Allele counts for population B.
Returns
-------
num : ndarray, shape (n_variants,), float
Numerator.
den : ndarray, shape (n_variants,), float
Denominator.
Notes
-----
See Patterson (2012), Appendix A.
TODO check if this is numerically equivalent to Hudson's estimator.
"""
from allel.stats.admixture import patterson_f2, h_hat
num = patterson_f2(aca, acb)
den = num + h_hat(aca) + h_hat(acb)
return num, den