Exploring Population Structure with Admixture Models and Principal Component Analysis
Chi‐Chun Liu, Suyash Shringarpure, Kenneth Lange, John Novembre
Abstract
Population structure is a commonplace feature of genetic variation data, and it has importance in numerous application areas, including evolutionary genetics, conservation genetics, and human genetics. Understanding the structure in a sample is necessary before more sophisticated analyses are undertaken. Here we provide a protocol for running principal component analysis (PCA) and admixture proportion inference-two of the most commonly used approaches in describing population structure. Along with hands-on examples with CEPH-Human Genome Diversity Panel and pragmatic caveats, readers will learn to analyze and visualize population structure on their own data.
Topics & Concepts
Principal component analysisInferencePopulationPopulation geneticsPopulation structureEvolutionary biologyComponent (thermodynamics)BiologyComputer scienceArtificial intelligenceDemographyThermodynamicsSociologyPhysicsGenetic diversity and population structureGenetic Mapping and Diversity in Plants and AnimalsGenetic and phenotypic traits in livestock