Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution-giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, researchers from Baylor College of Medicine review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.
Qualitative overview of structural variant calling methodology
using short reads and long reads and their associated costs
a, A qualitative comparison of the different SV methodologies ranging across technologies (whole genome and RNA-Seq using short and long reads) to different approaches (mapping vs. assembly) with respect to their costs and recall. b, The ratio of improvement in the number of SVs detected from using long reads across four human and two non-human studies. Overall, each study shows a clear improvement of using the longer reads.