RF-Net 2

RF-Net 2 infers reassortment and hybridization networks from discordant, error-prone gene/locus trees to reconstruct evolutionary histories of segmented RNA viruses such as influenza A virus (IAV).

Key Features:

• Enhanced Reticulation Handling: Implements Fast-RF-Net for efficient large-scale reticulation analysis in segmented RNA viruses like IAV.
• Automatic Stopping Criteria: Determines optimal reticulation count via heuristic stopping criteria.
• Error Correction: Outputs error-corrected gene trees to improve network reliability.
• Input Requirements: Requires rooted Newick-formatted gene/locus trees as input.

Scientific Applications:

• Virology: Infers reassortment and hybridization networks for segmented RNA viruses such as influenza A virus (IAV).

Methodology:

Reconstructs reassortment and hybridization networks from discordant gene trees using Fast-RF-Net for reticulation analysis, applies heuristic stopping criteria to select reticulation count, and produces error-corrected gene trees.