RT Journal Article
SR Electronic
T1 Joint Estimation of Pedigrees and Effective Population Size Using Markov Chain Monte Carlo
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 492678
DO 10.1101/492678
A1 Amy Ko
A1 Rasmus Nielsen
YR 2018
UL http://biorxiv.org/content/early/2018/12/10/492678.abstract
AB 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 (Ne), 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 Ne from genetic markers using Markov Chain Monte Carlo. Our method supports analysis of a large number of markers and individuals 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 Ne with high accuracy. We also apply the method on a real dataset of house sparrows to reconstruct their previously unreported pedigree.