Broccoli

Broccoli assigns orthologous groups and orthologous pairs among proteins using ultra-fast phylogenetic analyses and a network-based, parameter-free label propagation algorithm to improve orthology inference for comparative genomics and evolutionary studies.

Key Features:

• Phylogenetic Analysis: Performs ultra-fast phylogenetic analyses across proteins to provide a foundation for orthology inference.
• Network-Based Orthology Assignment: Constructs a phylogenetic network and applies a parameter-free machine learning label propagation algorithm to identify orthologous groups and orthologous pairs.
• Detection of Chimeric Proteins: Detects chimeric proteins arising from gene-fusion events and assigns their constituent parts to the corresponding orthologous groups.
• Performance and Scalability: Exhibits runtime efficiency comparable to recent distance-based methods and demonstrates superior performance in benchmark comparisons with existing orthology pipelines.

Scientific Applications:

• Comparative Genomics: Provides precise orthology assignments to support genome comparisons across species for evolutionary and comparative analyses.
• Functional Annotation: Supports annotation of gene functions by identifying orthologous groups for transfer of functional information.
• Evolutionary Biology: Enables investigation of evolutionary mechanisms such as gene fusion through detection of chimeric proteins and accurate orthology assignments.

Methodology:

Performs ultra-fast phylogenetic analyses to build a phylogenetic network, applies a parameter-free label propagation machine learning algorithm to identify orthologous groups and pairs, and detects chimeric proteins resulting from gene-fusion events.