z-logo
open-access-imgOpen Access
Misannotation of multiple-nucleotide variants risks misdiagnosis
Author(s) -
Matthew N. Wakeling,
Thomas W Laver,
Kevin Colclough,
Andrew Parish,
Sian Ellard,
Emma L. Baple
Publication year - 2020
Publication title -
wellcome open research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.298
H-Index - 21
ISSN - 2398-502X
DOI - 10.12688/wellcomeopenres.15420.2
Subject(s) - sanger sequencing , computational biology , pipeline (software) , computer science , dna sequencing , mutation , substitution (logic) , genetics , biology , data mining , gene , programming language
Multiple Nucleotide Variants (MNVs) are miscalled by the most widely utilised next generation sequencing analysis (NGS) pipelines, presenting the potential for missing diagnoses. These variants, which should be treated as a single insertion-deletion mutation event, are commonly called as separate single nucleotide variants. This can result in misannotation, incorrect amino acid predictions and potentially false positive and false negative diagnostic results. Using simulated data and re-analysis of sequencing data from a diagnostic targeted gene panel, we demonstrate that the widely adopted pipeline, GATK best practices, results in miscalling of MNVs and that alternative tools can call these variants correctly. The adoption of calling methods that annotate MNVs correctly would present a solution for individual laboratories, however GATK best practices are the basis for important public resources such as the gnomAD database. We suggest integrating a solution into these guidelines would be the optimal approach.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here