Year: 2019
Type: article
Abstract: Pedigrees provide the genealogical relationships among individuals at a fine resolution and serve an important function in many areas of genetic studies. One such use of pedigree information is in the estimation of the short-term effective population size [Formula: see text], which is of great relevance in fields such as conservation genetics. Despite the usefulness of pedigrees, however, they are often an unknown parameter and must be inferred from genetic data. In this study, we present a Bayesian method to jointly estimate pedigrees and [Formula: see text] from genetic markers using Markov Chain Monte Carlo. Our method supports analysis of a large number of markers and individuals within a single generation with the use of a composite likelihood, which significantly increases computational efficiency. We show, on simulated data, that our method is able to jointly estimate relationships up to first cousins and [Formula: see text] with high accuracy. We also apply the method on a real dataset of house sparrows to reconstruct their previously unreported pedigree.
Source: Genetics
Authors: Amy Ko, Rasmus Nielsen
Institutions: University of California, Berkeley, University of Copenhagen
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: bronze
Funder: Lundbeckfonden
Award: G2558956044
OpenAlex ID: W2952762977