Fast and accurate population admixture inference from genotype data from a few microsatellites to millions of SNPs.

ABSTRACT: Model-based (likelihood and Bayesian) and non-model-based (PCA and K-means clustering) methods were developed to identify populations and assign individuals to the identified populations using marker genotype data. Model-based methods are favoured because they are based on a probabilistic model of population genetics with biologically meaningful parameters and thus produce results that are easily interpretable and applicable. Furthermore, they often yield more accurate structure inferences than non-model-based methods. However, current model-based methods either are computationally demanding and thus applicable to small problems only or use simplified admixture models that could yield inaccurate results in difficult situations such as unbalanced sampling. In this study, I propose new likel

SUBMITTER: Wang J 

PROVIDER: S-EPMC9338324 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature