On the limits of fitting complex models of population history to f-statistics

Our understanding of population history in deep time has been assisted by fitting admixture graphs (AGs) to data: models that specify the ordering of population splits and mixtures, which along with the amount of genetic drift and the proportions of mixture, is the only information needed to predict the patterns of allele frequency correlation among populations. The space of possible AGs relating populations is vast, and thus most published studies have identified fitting AGs through a manual process driven by prior hypotheses, leaving the majority of alternative models unexplored. Here, we develop a method for systematically searching the space of all AGs that can incorporate non-genetic information in the…

• JT
  John Templeton Foundation

  Awards: grant 61220, 61220
• MŠ
  Ministerstvo Školství, Mládeže a Tělovýchovy

  Awards: LTAUSA18153, LM2015070, LL2103
• GA
  Grantová Agentura České Republiky

  Awards: LM2015070, 21-27624S
• NI
  National Institutes of Health

  Awards: HG012287, GM100233
• NS
  National Supercomputing Center, Korea Institute of Science and Technology Information