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- W2891909641 endingPage "2834" @default.
- W2891909641 startingPage "2819" @default.
- W2891909641 abstract "A key question in molecular evolutionary biology concerns the relative roles of mutation and selection in shaping genomic data. Moreover, features of mutation and selection are heterogeneous along the genome and over time. Mechanistic codon substitution models based on the mutation–selection framework are promising approaches to separating these effects. In practice, however, several complications arise, since accounting for such heterogeneities often implies handling models of high dimensionality (e.g., amino acid preferences), or leads to across-site dependence (e.g., CpG hypermutability), making the likelihood function intractable. Approximate Bayesian Computation (ABC) could address this latter issue. Here, we propose a new approach, named Conditional ABC (CABC), which combines the sampling efficiency of MCMC and the flexibility of ABC. To illustrate the potential of the CABC approach, we apply it to the study of mammalian CpG hypermutability based on a new mutation-level parameter implying dependence across adjacent sites, combined with site-specific purifying selection on amino-acids captured by a Dirichlet process. Our proof-of-concept of the CABC methodology opens new modeling perspectives. Our application of the method reveals a high level of heterogeneity of CpG hypermutability across loci and mild heterogeneity across taxonomic groups; and finally, we show that CpG hypermutability is an important evolutionary factor in rendering relative synonymous codon usage. All source code is available as a GitHub repository (https://github.com/Simonll/LikelihoodFreePhylogenetics.git)." @default.
- W2891909641 created "2018-09-27" @default.
- W2891909641 creator A5014774866 @default.
- W2891909641 creator A5020417939 @default.
- W2891909641 creator A5043933469 @default.
- W2891909641 creator A5057909697 @default.
- W2891909641 date "2018-09-07" @default.
- W2891909641 modified "2023-10-17" @default.
- W2891909641 title "Conditional Approximate Bayesian Computation: A New Approach for Across-Site Dependency in High-Dimensional Mutation–Selection Models" @default.
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