Inferring whole-genome histories in large population datasets.

ABSTRACT: Inferring the full genealogical history of a set of DNA sequences is a core problem in evolutionary biology, because this history encodes information about the events and forces that have influenced a species. However, current methods are limited, and the most accurate techniques are able to process no more than a hundred samples. As datasets that consist of millions of genomes are now being collected, there is a need for scalable and efficient inference methods to fully utilize these resources. Here we introduce an algorithm that is able to not only infer whole-genome histories with comparable accuracy to the state-of-the-art but also process four orders of magnitude more sequences. The approach also provides an 'evolutionary encoding' of the data, enabling efficient calculation of releva

SUBMITTER: Kelleher J 

PROVIDER: S-EPMC6726478 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature