Bolotie

Bolotie detects recombination events in viral genomes to identify inter-clade recombination and sequence anomalies within large datasets of highly similar sequences such as SARS-CoV-2.

Key Features:

• Rapid detection: Identifies inter-clade recombination events across extensive datasets and can analyze novel isolates in seconds.
• Handling high sequence similarity: Operates on datasets with low divergence and high similarity, demonstrated by detecting 225 anomalous SARS-CoV-2 genomes from 87,695 sequences.
• Comprehensive analysis: Detects recombination and other sequence anomalies and supports analysis of novel sequences without requiring a complete protocol rerun.
• Validation against co-infections: When raw sequencing data are available, examines underlying sequence reads to exclude co-infection as an alternative explanation for recombination signals.

Scientific Applications:

• Phylogenetic analysis: Improves accuracy of phylogenetic studies by identifying recombination events that can confound tree inference.
• Epidemiological forecasting: Informs epidemiological models by identifying recombinant strains that may alter transmission dynamics or pathogen behavior.
• Therapeutic development and public health policy: Supports evaluation of variants that could affect virulence or resistance, informing therapeutics and public health decisions.

Methodology:

Implements an algorithm to detect inter-clade recombination across large viral sequence datasets of near-identical genomes and, when available, inspects underlying raw sequencing reads to distinguish recombination from co-infection.