Nebula: Ultra-efficient mapping-free structural variant genotyper

Abstract

AbstractMotivationLarge scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping events in repeat regions. Thus we are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches.ResultsOur method Nebula utilizes the changes in the count of k-mers to predict the genotype of common structural variations. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping deletions and mobile-element insertions, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event.AvailabilityNebula is publicly available at https://github.com/Parsoa/NebulousSerendipity