FastMulRFS

FastMulRFS estimates species trees from multi-copy gene trees by solving the Robinson-Foulds supertree problem for MUL-trees to account for gene duplication and loss (GDL).

Key Features:

• Polynomial-Time Efficiency: Operates in polynomial time, enabling faster species tree estimation than comparable methods such as MulRF and ASTRAL-multi.
• MUL-tree Supertree (MulRF) Approach: Solves the Robinson-Foulds supertree problem tailored for MUL-trees to integrate multi-copy gene trees into a species tree.
• No Requirement for Orthology Knowledge: Estimates species trees without prior orthology assignment, preserving multi-copy gene data and paralogs.
• Statistical Consistency under GDL: Is statistically consistent under a generic model of gene duplication and loss (GDL) provided adversarial duplication and loss events do not occur.
• High Accuracy on Heterogeneous Datasets: Matches the accuracy of MulRF and outperforms other approaches including ASTRAL-multi on simulated large and heterogeneous datasets.

Scientific Applications:

• Species Tree Inference under GDL: Inferring species trees from phylogenomic datasets affected by gene duplication and loss.
• Large-Scale Phylogenomics: Analyzing large, heterogeneous genomic datasets that contain multi-copy gene families without discarding paralogs.

Methodology:

FastMulRFS solves the Robinson-Foulds supertree problem for MUL-trees (MulRF) using a polynomial-time algorithm to integrate multi-copy gene trees into a species tree.