Estimation of Cross-Species Introgression Rates Using Genomic Data Despite Model Unidentifiability.

ABSTRACT: Full-likelihood implementations of the multispecies coalescent with introgression (MSci) model treat genealogical fluctuations across the genome as a major source of information to infer the history of species divergence and gene flow using multilocus sequence data. However, MSci models are known to have unidentifiability issues, whereby different models or parameters make the same predictions about the data and cannot be distinguished by the data. Previous studies of unidentifiability have focused on heuristic methods based on gene trees and do not make an efficient use of the information in the data. Here we study the unidentifiability of MSci models under the full-likelihood methods. We characterize the unidentifiability of the bidirectional introgression (BDI) model, which assumes that

SUBMITTER: Yang Z 

PROVIDER: S-EPMC9087891 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature