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MultiWaverX: modeling latent sex-biased admixture history.

Rui ZhangXumin NiKai YuanYuwen PanShuhua Xu
Published in: Briefings in bioinformatics (2022)
Sex-biased gene flow has been common in the demographic history of modern humans. However, the lack of sophisticated methods for delineating the detailed sex-biased admixture process prevents insights into complex admixture history and thus our understanding of the evolutionary mechanisms of genetic diversity. Here, we present a novel algorithm, MultiWaverX, for modeling complex admixture history with sex-biased gene flow. Systematic simulations showed that MultiWaverX is a powerful tool for modeling complex admixture history and inferring sex-biased gene flow. Application of MultiWaverX to empirical data of 17 typical admixed populations in America, Central Asia, and the Middle East revealed sex-biased admixture histories that were largely consistent with the historical records. Notably, fine-scale admixture process reconstruction enabled us to recognize latent sex-biased gene flow in certain populations that would likely be overlooked by much of the routine analysis with commonly used methods. An outstanding example in the real world is the Kazakh population that experienced complex admixture with sex-biased gene flow but in which the overall signature has been canceled due to biased gene flow from an opposite direction.
Keyphrases
  • genome wide
  • copy number
  • genetic diversity
  • genome wide identification
  • machine learning
  • gene expression
  • artificial intelligence
  • electronic health record
  • clinical practice
  • genome wide analysis
  • big data