GAVIN: Gene-Aware Variant INterpretation for medical sequencing

Research output: Contribution to journalArticle

Abstract

We present Gene-Aware Variant INterpretation (GAVIN), a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%. This accuracy is unmatched by 12 other tools. We provide GAVIN as an online MOLGENIS service to annotate VCF files and as an open source executable for use in bioinformatic pipelines. It can be found at http://molgenis.org/gavin.

Details

Authors
  • K. Joeri van der Velde
  • Eddy N. de Boer
  • Cleo C. van Diemen
  • Birgit Sikkema-Raddatz
  • Kristin M. Abbott
  • Alain Knopperts
  • Lude Franke
  • Rolf H. Sijmons
  • Tom J. de Koning
  • Cisca Wijmenga
  • Richard J. Sinke
  • Morris A. Swertz
External organisations
  • University Medical Center Groningen
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Bioinformatics and Systems Biology
  • Medical Genetics

Keywords

  • Allele frequency, Automated protocol, Clinical next-generation sequencing, Gene-specific calibration, Pathogenicity prediction, Protein impact, Variant classification
Original languageEnglish
Article number6
JournalGenome Biology
Volume18
Issue number1
Publication statusPublished - 2017 Jan 16
Publication categoryResearch
Peer-reviewedYes
Externally publishedYes