A Machine-Learning-Based Approach to Prediction of Biogeographic Ancestry within Europe.

ABSTRACT: Data obtained with the use of massive parallel sequencing (MPS) can be valuable in population genetics studies. In particular, such data harbor the potential for distinguishing samples from different populations, especially from those coming from adjacent populations of common origin. Machine learning (ML) techniques seem to be especially well suited for analyzing large datasets obtained using MPS. The Slavic populations constitute about a third of the population of Europe and inhabit a large area of the continent, while being relatively closely related in population genetics terms. In this proof-of-concept study, various ML techniques were used to classify DNA samples from Slavic and non-Slavic individuals. The primary objective of this study was to empirically evaluate the feasibility of

SUBMITTER: Kloska A 

PROVIDER: S-EPMC10606184 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature