TreeShrink

TreeShrink detects outlier long branches in collections of phylogenetic trees by identifying sequences that artificially inflate tree diameter.

Key Features:

• Exact k-shrink algorithm: Finds k leaves whose removal maximally reduces tree diameter in polynomial time.
• Statistical outlier detection: Uses multiple statistical tests to identify species with unexpectedly high impact on tree diameter.
• Single-tree and multi-tree analysis: Can operate on a single tree or a set of related gene trees.
• Species-specific branch length adjustment: Accommodates species-specific patterns of branch length variation.
• Conservative filtering: Removes sequences more conservatively than rogue taxon removal methods.

Scientific Applications:

• Phylogenomic data quality control: Detects and removes erroneous sequences that produce unrealistically long branch lengths in phylogenetic trees.
• Gene tree discordance reduction: Reduces gene tree discordance when filtering levels are controlled.
• HIV phylogenetics: Identifies problematic sequences in HIV datasets.

Methodology:

TreeShrink builds a phylogeny including all data, detects sequences that inflate tree diameter, formulates and solves the k-shrink optimization problem to find leaves whose removal maximally reduces tree diameter, and applies statistical tests to identify outlier species with unexpectedly high impact on tree diameter.