wQFM

wQFM estimates species trees by amalgamating weighted quartets derived from estimated gene trees to resolve gene tree–species tree discordance caused by incomplete lineage sorting (ILS).

Key Features:

• Weighted Quartet FM extension: Extends the Quartet FM (QFM) algorithm into a weighted framework to incorporate quartet weights into tree inference.
• Input data: Accepts a set of estimated gene trees as input for downstream quartet generation.
• Weighted quartet generation: Produces weighted quartets that reflect relative support from the input gene trees.
• Quartet amalgamation: Amalgamates weighted quartets to construct a full-species tree for the taxonomic dataset.
• Heuristic optimization: Employs a heuristic approach aimed at minimizing the distance between the inferred species tree and the collection of weighted quartet trees.
• Statistical consistency: Provides statistical consistency for species tree estimation under conditions influenced by ILS.
• Empirical validation and scalability: Applied to simulated and real datasets, including a large avian phylogenomic dataset, demonstrating capability with extensive genomic data.
• Comparative performance: Reported to match or surpass methods such as wQMC (weighted Quartet Maximum Compatibility) and ASTRAL in comparative studies.

Scientific Applications:

• Phylogenomics: Estimating species trees from multi-locus genomic data where gene tree discordance due to ILS is a concern.
• Empirical dataset analysis: Analysis of large-scale datasets such as avian phylogenomic collections.
• Simulation studies: Assessment and benchmarking of species tree inference methods using simulated gene trees.

Methodology:

Extends QFM into a weighted framework, takes estimated gene trees to generate weighted quartets, amalgamates those quartets into a species tree using a heuristic that minimizes distance to the quartet set, and is claimed to be statistically consistent under ILS.