SVXplorer: Identification of structural variants through overlap of discordant clusters

Abstract

MotivationThe identification of structural variants using short-read data remains challenging. Most approaches ignore signatures of complex variants such as those generated by trans-posable elements. This can result in lower precision and sensitivity in identification of the more common structural variants such as deletions and duplications.\n\nResultsWe present SVXplorer, which uses a streamlined sequential approach to integrate discordant paired-end alignments with split-reads and read depth information. We show that it outperforms several existing approaches in both reproducibility and accuracy on real and simulated datasets.\n\nAvailabilitySVXplorer is available at https://github.com/kunalkathuria/SVXplorer.