HardyWeinberg (version 1.7.8)

HWAIC: Compute Akaike's Information Criterion (AIC) for HWP and EAF models

Description

Function HWAIC calculates Akaike's Information Criterion for ten different models that describe a bi-allelic genetic variant: M11: Hardy-Weinberg proportions and equality of allele frequencies in the sexes (HWP & EAF); M12: EAF and HWP in males only; M13: EAF and HWP in females only; M14: EAF and equality of inbreeding coefficients in the sexes (EIC); M15: EAF only; M21: HWP in both sexes; M22: HWP for males only; M23: HWP for females only; M24: EIC only; M25: None of the previous.

Usage

HWAIC(x, y, tracing = 0, tol = 0.000001)

Value

A named vector containing 6 values for AIC

Arguments

x

Male genotype counts (AA,AB,BB)

y

Female genotype counts (AA,AB,BB)

tracing

Activate tracing in the maximization of some likelihoods (0=no tracing; 1:tracing)

tol

tolerance for iterative maximization of some likelihoods

Author

Jan Graffelman

Details

The log-likelihood for the six models is calculated. For two models (C and E) this is done numerically using package RSolnp.

References

Graffelman, J. and Weir, B.S. (2018) On the testing of Hardy-Weinberg proportions and equality of allele frequencies in males and females at bi-allelic genetic markers. Genetic Epidemiology 42(1) pp. 34-48. tools:::Rd_expr_doi("10.1002/gepi.22079")

See Also

HWLRtest

Examples

males <- c(AA=11,AB=32,BB=13) 
females <- c(AA=14,AB=23,BB=11) 
stats <- HWAIC(males,females)
print(stats)