Applying f4 -statistics and admixture graphs: Theory and examples

Mol Ecol Resour. 2020 Nov;20(6):1658-1667. doi: 10.1111/1755-0998.13230. Epub 2020 Aug 19.


A popular approach to learning about admixture from population genetic data is by computing the allele-sharing summary statistics known as f-statistics. Compared to some methods in population genetics, f-statistics are relatively simple, but interpreting them can still be complicated at times. In addition, f-statistics can be used to build admixture graphs (multi-population trees allowing for admixture events), which provide more explicit and thorough modelling capabilities but are correspondingly more complex to work with. Here, I discuss some of these issues to provide users of these tools with a basic guide for protocols and procedures. My focus is on the kinds of conclusions that can or cannot be drawn from the results of f4 -statistics and admixture graphs, illustrated with real-world examples involving human populations.

Keywords: admixture; admixture graphs; f-statistics; parameter estimation.

MeSH terms

  • Genetics, Population*
  • Humans
  • Models, Genetic*