A recurrence-based approach for validating structural variation using long-read sequencing technology.

ABSTRACT: Although numerous algorithms have been developed to identify structural variations (SVs) in genomic sequences, there is a dearth of approaches that can be used to evaluate their results. This is significant as the accurate identification of structural variation is still an outstanding but important problem in genomics. The emergence of new sequencing technologies that generate longer sequence reads can, in theory, provide direct evidence for all types of SVs regardless of the length of the region through which it spans. However, current efforts to use these data in this manner require the use of large computational resources to assemble these sequences as well as visual inspection of each region. Here we present VaPoR, a highly efficient algorithm that autonomously validates large SV sets

SUBMITTER: Zhao X 

PROVIDER: S-EPMC5737365 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature