Improving quartet graph construction for scalable and accurate species tree estimation from gene trees.

ABSTRACT: methods are widely used to estimate species trees from genome-scale data. However, they can fail to produce accurate species trees when the input gene trees are highly discordant because of estimation error and biological processes, such as incomplete lineage sorting. Here, we introduce TREE-QMC, a new summary method that offers accuracy and scalability under these challenging scenarios. TREE-QMC builds upon weighted Quartet Max Cut, which takes weighted quartets as input and then constructs a species tree in a divide-and-conquer fashion, at each step forming a graph and seeking its max cut. The wQMC method has been successfully leveraged in the context of species tree estimation by weighting quartets by their frequencies in the gene trees; we improve upon this approach in two ways. First,

SUBMITTER: Han Y 

PROVIDER: S-EPMC10538498 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature