Faster inference of complex demographic models from large allele frequency spectra

Abstract

We present O_SCPLOWMOMIC_SCPLOW3, a new method for inferring complex demographic models using genetic variation data sampled from many populations. O_SCPLOWMOMIC_SCPLOW3 features many improvements over its predecessor O_SCPLOWMOMIC_SCPLOW2 (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 1000x over existing state-of-the-art methods such as {partial}a{partial}i, O_SCPLOWMOMENTSC_SCPLOW, and O_SCPLOWMOMIC_SCPLOW2. 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.