MSCquartetsR

MSCquartetsR implements species-tree and species-network inference and hypothesis testing under the multispecies coalescent model by summarizing metric or topological gene/locus trees into quartets to address incomplete lineage sorting (ILS).

Key Features:

• Species Tree Hypothesis Testing: Performs hypothesis tests on species-tree topologies using collections of metric or topological gene or locus trees and displays results as simplex plots with color-coded points at specified significance levels.
• QDC (Quartet Distance Criterion): Provides a statistically consistent algorithm for species-tree inference from quartet summaries under the multispecies coalescent.
• WQDC (Weighted Quartet Distance Criterion): Extends QDC by incorporating quartet weights for improved metric species-tree inference.
• NANUQ (Network ANalysis Using QUartets): Infers level-1 topological species networks from quartet summaries to capture reticulate evolutionary relationships.
• Data Input and Summarization: Processes collections of metric or topological locus or gene trees and summarizes them via the quartets displayed on those trees.

Scientific Applications:

• Phylogenetic Analysis: Improves reconstruction of species relationships by accounting for gene tree discordance caused by incomplete lineage sorting under the multispecies coalescent.
• Evolutionary Network Studies: Enables detection and representation of reticulate evolution and hybridization through level-1 species-network inference from quartet data.

Methodology:

Implements the multispecies coalescent model, summarizes gene/locus trees into quartets, performs quartet-based hypothesis tests with simplex plots, and applies QDC, WQDC, and NANUQ algorithms for species-tree and level-1 species-network inference.