ArticleTheoretical population biology2011
Inference on the strength of balancing selection for epistatically interacting loci.
Article in Theoretical population biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Inference from the stationary distribution of allele frequencies in a family of Wright-Fisher models with two levels of genetic variability.Theoretical population biology · 2018Article
- Article
- KIR and HLA under pressure: evidences of coevolution across worldwide populations.Human genetics · 2015Review
- Recent human adaptation: genomic approaches, interpretation and insights.Nature reviews. Genetics · 2013Review
- Omics technologies and the study of human ageing.Nature reviews. Genetics · 2013Review
- An explicit transition density expansion for a multi-allelic Wright-Fisher diffusion with general diploid selection.Theoretical population biology · 2013Article
- Efficient simulation and likelihood methods for non-neutral multi-allele models.Journal of computational biology : a journal of computational molecular cell biology · 2012Article
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3 authors.
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Abstract
Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods.
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