Cheng Ye

RIVET identifies and tracks potential SARS-CoV-2 recombinants using advanced algorithms and provides a web interface for accelerated analysis.

The paper develops a phylogenetic package to handle pandemic-scale SARS-CoV-2 genomic data, enabling real-time analysis and visualization of large mutation-annotated phylogenetic trees.

This study compares online and de novo phylogenetic methods for SARS-CoV-2, finding that maximum parsimony online approaches are more accurate and efficient than maximum likelihood or de novo methods.