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GAVIN : Gene-Aware Variant INterpretation for medical sequencing

van der Velde, K. Joeri ; de Boer, Eddy N. ; van Diemen, Cleo C. ; Sikkema-Raddatz, Birgit ; Abbott, Kristin M. ; Knopperts, Alain ; Franke, Lude ; Sijmons, Rolf H. ; de Koning, Tom J. LU and Wijmenga, Cisca , et al. (2017) In Genome Biology 18(1).
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.

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publishing date
type
Contribution to journal
publication status
published
subject
keywords
Allele frequency, Automated protocol, Clinical next-generation sequencing, Gene-specific calibration, Pathogenicity prediction, Protein impact, Variant classification
in
Genome Biology
volume
18
issue
1
article number
6
publisher
BioMed Central (BMC)
external identifiers
  • pmid:28093075
  • scopus:85010014418
ISSN
1474-7596
DOI
10.1186/s13059-016-1141-7
language
English
LU publication?
no
id
236dffbe-a4cd-4a2b-a4de-b384d6ef03b4
date added to LUP
2020-02-26 09:51:53
date last changed
2024-01-16 21:50:22
@article{236dffbe-a4cd-4a2b-a4de-b384d6ef03b4,
  abstract     = {{<p>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 &gt;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.</p>}},
  author       = {{van der Velde, K. Joeri and de Boer, Eddy N. and van Diemen, Cleo C. and Sikkema-Raddatz, Birgit and Abbott, Kristin M. and Knopperts, Alain and Franke, Lude and Sijmons, Rolf H. and de Koning, Tom J. and Wijmenga, Cisca and Sinke, Richard J. and Swertz, Morris A.}},
  issn         = {{1474-7596}},
  keywords     = {{Allele frequency; Automated protocol; Clinical next-generation sequencing; Gene-specific calibration; Pathogenicity prediction; Protein impact; Variant classification}},
  language     = {{eng}},
  month        = {{01}},
  number       = {{1}},
  publisher    = {{BioMed Central (BMC)}},
  series       = {{Genome Biology}},
  title        = {{GAVIN : Gene-Aware Variant INterpretation for medical sequencing}},
  url          = {{http://dx.doi.org/10.1186/s13059-016-1141-7}},
  doi          = {{10.1186/s13059-016-1141-7}},
  volume       = {{18}},
  year         = {{2017}},
}