A model-free method for genealogical inference without phasing and its application for topology weighting.

ABSTRACT: Recent advances in methods to infer and analyze ancestral recombination graphs (ARGs) are providing powerful new insights in evolutionary biology and beyond. Existing inference approaches tend to be designed for use with fully phased datasets, and some rely on model assumptions about demography and recombination rate. Here I describe a simple model-free approach for genealogical inference along the genome from unphased genotype data called Sequential Tree Inference by Collecting Compatible Sites (sticcs). sticcs applies a heuristic algorithm based on the perfect phylogeny principle to reconstruct a local genealogy at each variant site in the genome, using a "collecting" procedure to import information from other nearby sites. Using simulations, I show that sticcs is accurate for ARG infere

SUBMITTER: Martin SH 

PROVIDER: S-EPMC12774849 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature