Optimizing genomic sampling for demographic and epidemiological inference with Markov decision processes.

ABSTRACT: Inferences from population genomic data provide valuable insights into the demographic history of a population. Likewise, in genomic epidemiology, pathogen genomic data provide key insights into epidemic dynamics and potential sources of transmission. Yet, predicting what information will be gained from genomic data about variables of interest and how different sampling strategies will impact the quality of downstream inferences remains challenging. As a result, population genomics and related fields such as phylodynamics and phylogeography largely lack theory to guide decisions on how best to sample individuals for genomic sequencing. By adopting a sequential decision making framework based on Markov decision processes, we model how sampling interacts with a population's demographic histo

SUBMITTER: Rasmussen DA 

PROVIDER: S-EPMC12774829 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature