Hierarchical Models for Mitochondrial DNA Sequence Data

Paola Berchialla

doi:10.17713/ajs.v36i1.320

Authors

Paola Berchialla University of Torino, Italy

DOI:

https://doi.org/10.17713/ajs.v36i1.320

Abstract

We introduce a Bayesian hierarchical model for mitochondrial DNA sequence data, which is fitted via acceptance-rejection algorithms. The model incorporates parametric models of population history explicitly as well as a mutational process allowing for a simultaneous parameter estimation whose importance has become increasingly clear in many recent studies. The model is applied to a sample of DNA sequences from the Italian population.

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