The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Understanding admixture fractions: theory and estimation of gene-flow
Abstract
Estimation of admixture fractions has become one of the most commonly used computational tools in population genomics. How ever, there is remarkably little population genetic theory on their statistical properties. We develop theoretical results that can accurately predict means and variances of admixture proportions within a population using models with recombination and genetic drift. Based on established theory on measures of multilocus disequilibrium, we show that there is a set of recurrence relations that can be used to derive expectations for higher moments of the admixture fraction distribution. We obtain closed form solutions for some special cases. Using these results, we develop a method for estimating admixture parameters from estimated admixture proportion obtained from programs such as Structure or Admixture. We apply this method to HapMap data and find that the population history of African Americans, as expected, is not best explained by a single admixture event between people of European and African ancestry. A model of constant gene flow for the past 11 generations until 2 generations ago gives a better fit.
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“indicating that it originates from very recent historical admixture without time to reach equilibrium across the population (15).”
From Message in a bottleneck: Nested founder effects from French Polynesia to Rapa Nui and Hawaiʻi (2026) · cites this paper as [15]
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Self-citation
Research works printed but not linked: 1
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Cited by
Message in a bottleneck: Nested founder effects from French Polynesia to Rapa Nui and Hawaiʻi
Shanks, C., Huang, E. C., Thomassin, C., Emde, A.-K., Rodière, V., Moraga, M., Sandoval, K., Merriman, T., Pascart, T., Moreno-Estrada, A., et al. (2026) · Science · doi:10.1126/science.aec7662
Metadata
- Authors
- Liang, M., Shishkin, M., Shchur, V., & Nielsen, R.
- ORCID
- Shchur, Vladimir
- Venue
- Journal of Mathematical Biology
- Published
- 2024-10-04
- Volume
- 89
- Issue
- 5
- ISSN
- 0303-6812
- 1432-1416
- PMC
- PMC12042791
- Cited by
- 5
- References
- 32
- Language
- en
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
- Funders
- Russian Science Foundation (22-71-10056)
- NIH (R01GM138634)
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