RECUR: identifying recurrent amino acid substitutions from multiple sequence alignments.

ABSTRACT: Identifying recurrent changes in biological sequences is important to multiple aspects of biological research-from understanding the molecular basis of convergent phenotypes, to pinpointing the causative sequence changes that give rise to antibiotic resistance and disease. Here, we present RECUR, a method for identifying recurrent amino acid substitutions from multiple sequence alignments that is fast, easy to use, and scalable to thousands of sequences. We demonstrate that RECUR's recurrence detection achieves 100% accuracy on simulated data with known evolutionary histories. We further show that RECUR is robust to realistic levels of tree inference error. Finally, we apply RECUR to a large set of surface glycoprotein (S) protein sequences from SARS-CoV-2. This analysis identified widespr

SUBMITTER: Robbins EHJ 

PROVIDER: S-EPMC12930092 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature