GAVIN: Gene-Aware Variant INterpretation for medical sequencing

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

doi:10.1186/s13059-016-1141-7

GAVIN: Gene-Aware Variant INterpretation for medical sequencing

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

Research output: Contribution to journal › Article › Academic › peer-review

52 Citations (Scopus)

403 Downloads (Pure)

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 .

Original language	English
Article number	6
Number of pages	10
Journal	Genome Biology
Volume	18
Issue number	1
DOIs	https://doi.org/10.1186/s13059-016-1141-7
Publication status	Published - 16-Jan-2017

Keywords

Clinical next-generation sequencing
Variant classification
Automated protocol
Gene-specific calibration
Allele frequency
Protein impact
Pathogenicity prediction
NONCODING VARIANTS
PATHOGENICITY
MUTATIONS
DATABASE
DISEASE
GENOME
MODEL
SCORE

Access to Document

10.1186/s13059-016-1141-7Licence: CC BY

GAVIN Gene-Aware Variant INterpretation for medical sequencingFinal publisher's version, 1.08 MBLicence: CC BY

Handle.net

Persistent link

Additional file 3: Table S3. of GAVIN: Gene-Aware Variant INterpretation for medical sequencing
van der Velde, J. (Contributor), de Boer, E. (Contributor), van Diemen, C. (Contributor), Raddatz, B. (Contributor), Abbott, K. (Contributor), Knopperts, A. (Contributor), Franke, L. (Contributor), Sijmons, R. (Contributor), de Koning, T. J. (Contributor), Wijmenga, C. (Contributor), Sinke, R. (Contributor) & Swertz, M. (Contributor), University of Groningen, 16-Jan-2017
DOI: 10.6084/m9.figshare.c.3666643_d3.v1
Dataset
Additional file 4: Table S4. of GAVIN: Gene-Aware Variant INterpretation for medical sequencing
van Diemen, C. (Contributor), Wijmenga, C. (Contributor), Franke, L. (Contributor), van der Velde, J. (Contributor), Sinke, R. (Contributor), Swertz, M. (Contributor), Raddatz, B. (Contributor), de Boer, E. (Contributor), Knopperts, A. (Contributor), de Koning, T. J. (Contributor), Sijmons, R. (Contributor) & Abbott, K. (Contributor), University of Groningen, 16-Jan-2017
DOI: 10.6084/m9.figshare.c.3666643_d1.v1
Dataset
Additional file 2: Table S2. of GAVIN: Gene-Aware Variant INterpretation for medical sequencing
de Koning, T. J. (Contributor), Sijmons, R. (Contributor), Raddatz, B. (Contributor), Swertz, M. (Contributor), de Boer, E. (Contributor), Wijmenga, C. (Contributor), Sinke, R. (Contributor), van Diemen, C. (Contributor), Knopperts, A. (Contributor), Franke, L. (Contributor), Abbott, K. (Contributor) & van der Velde, J. (Contributor), University of Groningen, 16-Jan-2017
DOI: 10.6084/m9.figshare.c.3666643_d2.v1
Dataset

Cite this

@article{51c07ba5cc8e48c6b141cd95af65a3f1,

title = "GAVIN: Gene-Aware Variant INterpretation for medical sequencing",

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 .",

keywords = "Clinical next-generation sequencing, Variant classification, Automated protocol, Gene-specific calibration, Allele frequency, Protein impact, Pathogenicity prediction, NONCODING VARIANTS, PATHOGENICITY, MUTATIONS, DATABASE, DISEASE, GENOME, MODEL, SCORE",

author = "{van der Velde}, {K Joeri} and {de Boer}, {Eddy N} and {van Diemen}, {Cleo C} and Birgit Sikkema-Raddatz and Abbott, {Kristin M} and Alain Knopperts and Lude Franke and Sijmons, {Rolf H} and {de Koning}, {Tom J} and Cisca Wijmenga and Sinke, {Richard J} and Swertz, {Morris A}",

year = "2017",

month = jan,

day = "16",

doi = "10.1186/s13059-016-1141-7",

language = "English",

volume = "18",

journal = "Genome Biology",

issn = "1465-6906",

publisher = "BMC",

number = "1",

}

TY - JOUR

T1 - GAVIN

T2 - Gene-Aware Variant INterpretation for medical sequencing

AU - van der Velde, K Joeri

AU - de Boer, Eddy N

AU - van Diemen, Cleo C

AU - Sikkema-Raddatz, Birgit

AU - Abbott, Kristin M

AU - Knopperts, Alain

AU - Franke, Lude

AU - Sijmons, Rolf H

AU - de Koning, Tom J

AU - Wijmenga, Cisca

AU - Sinke, Richard J

AU - Swertz, Morris A

PY - 2017/1/16

Y1 - 2017/1/16

N2 - 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 .

AB - 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 .

KW - Clinical next-generation sequencing

KW - Variant classification

KW - Automated protocol

KW - Gene-specific calibration

KW - Allele frequency

KW - Protein impact

KW - Pathogenicity prediction

KW - NONCODING VARIANTS

KW - PATHOGENICITY

KW - MUTATIONS

KW - DATABASE

KW - DISEASE

KW - GENOME

KW - MODEL

KW - SCORE

U2 - 10.1186/s13059-016-1141-7

DO - 10.1186/s13059-016-1141-7

M3 - Article

C2 - 28093075

SN - 1465-6906

VL - 18

JO - Genome Biology

JF - Genome Biology

IS - 1

M1 - 6

ER -

GAVIN: Gene-Aware Variant INterpretation for medical sequencing

Abstract

Keywords

Access to Document

Handle.net

Fingerprint

Datasets

Additional file 3: Table S3. of GAVIN: Gene-Aware Variant INterpretation for medical sequencing

Additional file 4: Table S4. of GAVIN: Gene-Aware Variant INterpretation for medical sequencing

Additional file 2: Table S2. of GAVIN: Gene-Aware Variant INterpretation for medical sequencing

Cite this