| Literature DB >> 36068478 |
I King Jordan1, Shivam Sharma2, Shashwat Deepali Nagar3, Augusto Valderrama-Aguirre4, Leonardo Mariño-Ramírez5.
Abstract
Genetic ancestry inference can be used to stratify patient cohorts and to model pharmacogenomic variation within and between populations. We provide a detailed guide to genetic ancestry inference using genome-wide genetic variant datasets, with an emphasis on two widely used techniques: principal components analysis (PCA) and ADMIXTURE analysis. PCA can be used for patient stratification and categorical ancestry inference, whereas ADMIXTURE is used to characterize genetic ancestry as a continuous variable. Visualization methods are critical for the interpretation of genetic ancestry inference methods, and we provide instructions for how the results of PCA and ADMIXTURE can be effectively visualized.Entities:
Keywords: Admixture; Genetic ancestry inference; Genetic variants; Health disparities; Pharmacogenomics; Population-specific drug efficacy
Mesh:
Year: 2022 PMID: 36068478 PMCID: PMC9486757 DOI: 10.1007/978-1-0716-2573-6_21
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745