MSCquartets

MSCquartets infers species trees and level-1 species networks and tests species-tree hypotheses under the multispecies coalescent (MSC) model by summarizing metric or topological locus trees with quartets to account for incomplete lineage sorting.

Key Features:

• Data input and processing: Accepts collections of metric or topological locus trees and summarizes them by the quartets they display.
• QDC (Quartet Distance Consensus): Infers topological species trees from quartet summaries under the MSC framework.
• WQDC (Weighted Quartet Distance Consensus): Infers metric species trees incorporating branch length information from quartet weights.
• NANUQ (Network ANalysis Using QUartets): Infers level-1 topological species networks to detect reticulate events such as hybridization or horizontal gene transfer.
• Statistical consistency: Implemented algorithms provide statistically consistent estimators under the multispecies coalescent model.
• Visualization: Hypothesis-test results are represented with simplex plots using color-coded points to indicate outcomes at specified significance levels.

Scientific Applications:

• Species tree hypothesis testing: Tests hypotheses about species relationships by comparing observed gene-tree quartet distributions to expectations under the MSC model.
• Inference of species trees and networks: Reconstructs bifurcating species trees and level-1 networks to investigate speciation and reticulation processes.

Methodology:

Accepts metric or topological locus trees, summarizes them via quartet counts, and analyzes quartet summaries using QDC, WQDC, and NANUQ algorithms under the multispecies coalescent model, with hypothesis-test results visualized in simplex plots.