Faster inference of complex demographic models from large allele frequency spectra

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Abstract

We present momi 3, a new method for inferring complex demographic models using genetic variation data sampled from many populations. momi 3 features many improvements over its predecessor momi 2 (Kamm, Terhorst, Durbin, et al., 2020), including support for continuous migration, just-in-time compilation, and execution on GPUs; a standardized interface for specifying demographic models; and a novel importance sampling strategy that enables it to efficiently analyze data from a large number of samples. Together, these improvements lead to speedups of as much as 1000× over existing state-of-the-art methods such as ∂ ai , moments , and momi 2. We illustrate the usefulness of our method by revisiting a model of archaic admixture using a large, recent dataset containing hundreds of human genomes from many populations.

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