Structural variant calling: the long and the short of it

By M. Mahmoud, Nastassia Gobet, Diana Ivette Cruz-Dávalos, Ninon Mounier, Christophe Dessimoz, Fritz J. Sedlazeck. Genome Biology, 2019

588 citations recorded by the source corpus.

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, we 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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b9e8ed710a4be1df8dcfbdb9570ec842e6a3065f

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In Molecular Biology

Citations in the corpus

Detection of mosaic and population-level structural variants with Sniffles2 (2024, unknown): “Sniffles2 remains open source (MIT license) and is available at https://github.com/fritzsedlazeck/Sniffles.”
Pangenomics enables genotyping known structural variants in 5,202 diverse genomes (2021, background): “Because of reference allele bias, SVs are much more poorly characterized than single-nucleotide variants (SNVs) and short insertions and deletions (collectively termed indels) ( 1 , 2 ).”