Accelerated Bayesian inference of population size history from recombining sequence data.

ABSTRACT: This study introduces population history learning by averaging sampled histories (PHLASH), a new method for inferring population history from whole-genome sequence data. It works by drawing random, low-dimensional projections of the coalescent intensity function from the posterior distribution of a pairwise sequentially Markovian coalescent-like model and averaging them together to form an accurate and adaptive estimator. On simulated data, PHLASH tends to be faster and have lower error than several competing methods, including SMC++, MSMC2 and FITCOAL. Moreover, it provides automatic uncertainty quantification and leads to new Bayesian testing procedures for detecting population structure and ancient bottlenecks. The key technical advance is a new algorithm for computing the score functio

SUBMITTER: Terhorst J 

PROVIDER: S-EPMC12513830 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature