Regularized sequence-context mutational trees capture variation in mutation rates across the human genome.

ABSTRACT: Germline mutation is the mechanism by which genetic variation in a population is created. Inferences derived from mutation rate models are fundamental to many population genetics methods. Previous models have demonstrated that nucleotides flanking polymorphic sites-the local sequence context-explain variation in the probability that a site is polymorphic. However, limitations to these models exist as the size of the local sequence context window expands. These include a lack of robustness to data sparsity at typical sample sizes, lack of regularization to generate parsimonious models and lack of quantified uncertainty in estimated rates to facilitate comparison between models. To address these limitations, we developed Baymer, a regularized Bayesian hierarchical tree model that captures th

SUBMITTER: Adams CJ 

PROVIDER: S-EPMC10355397 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature