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Ancestral recombination graphs

Matthias Steinrücken
UMass Amherst

A demography-aware conditional sampling distribution for inferring ancient demography and detecting introgression patterns

Matthias Steinrücken
Matthias Steinrücken

Complex demographic histories shape the genealogies of contemporary individuals and thus have a substantial impact on the genetic variation observed today. These genealogies are commonly modeled by the ancestral recombination graph (ARG), and we developed a novel demography-aware conditional sampling distribution (CSD) to approximate these ARGs under general demographic models. We apply this CSD in an expectation-maximization framework for demographic inference. We show that this method can accurately recover biologically relevant demographic parameters like population divergence times, migration rates, or ancestral population sizes from simulated datasets. Furthermore, we apply the CSD to detect tracts of genetic material that introgressed from Neanderthal into modern humans. Our results are in general agreement with previously published results, and we will discuss the similarities and differences, and their biological implications.