Login / Signup

Faster inference of complex demographic models from large allele frequency spectra.

Enes DilberJonathan Terhorst
Published in: bioRxiv : the preprint server for biology (2024)
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 ∂ a ∂ i , 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.
Keyphrases
  • electronic health record
  • endothelial cells
  • big data
  • induced pluripotent stem cells
  • genetic diversity
  • data analysis
  • pluripotent stem cells