MulRF

MulRF generalizes the Robinson-Foulds distance to multi-labeled gene trees and provides algorithms for species tree inference from collections of gene trees.

Key Features:

• Robinson-Foulds Distance Generalization: Extends the traditional Robinson-Foulds metric to accommodate multi-labeled trees with multiple copies per gene, enabling measurement of discrepancies among complex phylogenetic trees.
• Efficient Species Tree Inference: Implements algorithms optimized for handling large datasets of gene trees to infer species trees from extensive collections of genetic data.
• Customizable Search and Assessment: Provides customizable options for the species tree search process and tools for assessing and validating inferred phylogenies.
• Reconciliation of Gene Tree Discordance: Offers a framework to address gene tree discordance arising from processes such as gene duplication and hybridization.

Scientific Applications:

• Evolutionary biology and bioinformatics: Inferring species relationships from gene tree datasets to support comparative and evolutionary analyses.
• Gene duplication and hybridization studies: Analysing datasets with multiple gene copies and complex evolutionary histories involving duplication or hybridization events.
• Species tree reconstruction: Constructing species trees that reconcile discordant gene trees to improve phylogenetic accuracy.

Methodology:

Generalizes the Robinson-Foulds distance to multi-labeled trees; employs algorithms optimized for large collections of gene trees; offers configurable species tree search parameters and result-assessment tools.