The fundamental challenge of multi-sample structural variant (SV) analysis such as merging and benchmarking is identifying when two SVs are the same. Common approaches for comparing SVs were developed alongside technologies which produce ill-defined boundaries. As SV detection becomes more exact, algorithms to preserve this refined signal are needed. Here, we present Truvari-an SV comparison, annotation, and analysis toolkit-and demonstrate the effect of SV comparison choices by building population-level VCFs from 36 haplotype-resolved long-read assemblies. We observe over-merging from other SV merging approaches which cause up to a 2.2× inflation of allele frequency, relative to Truvari.
Keywords: SV annotation; SV benchmarking; SV comparison; SV merging; Structural variation.
© 2022. The Author(s).