Graph-based algorithms for Laplace transformed coalescence time distributions.

ABSTRACT: Extracting information on the selective and demographic past of populations that is contained in samples of genome sequences requires a description of the distribution of the underlying genealogies. Using the Laplace transform, this distribution can be generated with a simple recursive procedure, regardless of model complexity. Assuming an infinite-sites mutation model, the probability of observing specific configurations of linked variants within small haplotype blocks can be recovered from the Laplace transform of the joint distribution of branch lengths. However, the repeated differentiation required to compute these probabilities has proven to be a serious computational bottleneck in earlier implementations. Here, I show that the state space diagram can be turned into a computational g

SUBMITTER: Bisschop G 

PROVIDER: S-EPMC9514611 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature