Quantitative Biology 2017, 5(3): 236–250 DOI 10.1007/s40484-017-0117-2 REVIEW Models, methods and tools for ancestry inference and admixture analysis ,† ,† ,† Kai Yuan1,2 , Ying Zhou1,2 , Xumin Ni3 , Yuchen Wang1,2, Chang Liu1,2 and Shuhua Xu1,2,4,5,* 1 CAS Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, CAS, Shanghai 200031, China 2 University of Chinese Academy of Sciences, Beijing 100049, China 3 Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing 100044, China 4 School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China 5 Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China * Correspondence:
[email protected] Received May 5, 2017; Revised July 1, 2017; Accepted July 3, 2017 Background: Genetic admixture refers to the process or consequence of interbreeding between two or more previously isolated populations within a species. Compared to many other evolutionary driving forces such as mutations, genetic drift, and natural selection, genetic admixture is a quick mechanism for shaping population genomic diversity. In particular, admixture results in “recombination” of genetic variants that have been fixed in different populations, which has many evolutionary and medical implications. Results: However, it is challenging to accurately reconstruct population admixture history and to understand of population admixture dynamics. In this review, we provide an overview of models, methods, and tools for ancestry inference and admixture analysis. Conclusions: Many methods and tools used for admixture analysis were originally developed to analyze human data, but these methods can also be directly applied and/or slightly modified to study non-human species as well.