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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722024 | PMC |
| http://dx.doi.org/10.1007/978-1-0716-0199-0_4 | DOI Listing |
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