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Exploring Population Structure with Admixture Models and Principal Component Analysis
Chi-Chun Liu1, Suyash Shringarpure2, Kenneth Lange3,4,5
1Department of Human Genetics, University of Chicago, Chicago, IL, USA.
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.
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