TAILVAR (Terminal extension Analysis for Improved prediction of Lengthened VARiants)

TAILVAR is built using a Random Forest model that predicts the pathogenicity of stop-loss variants. By integrating a combination of in-silico prediction scores, transcript, and protein features of C-terminal extensions, TAILVAR provides a score ranging from 0 to 1, indicating the probability of pathogenic potential. TAILVAR score cutoffs ≥ 0.70 and ≤ 0.30 can be used to distinguish potential pathogenic/likely pathogenic and benign/likely benign variants. For more information, please visit https://github.com/dr-yoon/TAILVAR