Abstract
The Hardy-Weinberg equilibrium (HWE) assumption is essential to many population genetics models. Multiple tests were developed to test its applicability in observed genotypes. Current methods are divided into exact tests applicable to small populations and a small number of alleles, and approximate goodness-of-fit tests. Existing tests cannot handle ambiguous typing in multi-allelic loci. We here present a novel exact test Unambiguous Multi Allelic Test (UMAT) not limited to the number of alleles and population size, based on a perturbative approach around the current observations. We show its accuracy in the detection of deviation from HWE. We then propose an additional model to handle ambiguous typing using either sampling into UMAT or a goodness-of-fit test test with a variance estimate taking ambiguity into account, named Asymptotic Statistical Test with Ambiguity (ASTA). We show the accuracy of ASTA and the possibility of detecting the source of deviation from HWE. We apply these tests to the HLA loci to reproduce multiple previously reported deviations from HWE, and a large number of new ones.
Original language | English |
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Journal | Briefings in Bioinformatics |
Volume | 25 |
Issue number | 5 |
DOIs | |
State | Published - 25 Jul 2024 |
Bibliographical note
Publisher Copyright:© The Author(s) 2024. Published by Oxford University Press.
Keywords
- Gibbs sampling
- Hardy–Weinberg equilibrium
- imputation algorithms