VeChat: correcting errors in long reads using variation graphs

Abstract

Consensus sequence-based methods for self-correction of long-read sequencing data are affected by biases that can mask true variants characterizing little-covered or low-frequency haplotypes. Here, to address this issue, the authors develop a variation graph-based method for performing haplotype-aware self-correction of long reads.