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Inference on admixture fractions in a mechanistic model of recurrent admixture
Erkan Ozge Buzbas1, Paul Verdu2
1Department of Statistical Science, University of Idaho, United States.
Abstract:
Signatures of recent historical admixture are ubiquitous in human populations. We present a mechanistic model of admixture with two source populations, encompassing recurrent admixture periods and study the distribution of admixture fractions for finite but arbitrary genome size. We provide simulation-based methods to estimate the introgression parameters and discuss the implications of reaching stationarity on estimability of parameters when there are recurrent admixture events with different rates.
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