GAVIN: Gene-Aware Variant INterpretation for medical sequencing

By Joeri van der Velde, E. N. Boer, C. V. Diemen, B. Sikkema‐Raddatz, K. Abbott, A. Knopperts, Lude Franke, R. Sijmons, T. Koning, C. Wijmenga and 2 more. 2017

61 citations recorded by the source corpus.

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.

Subfields: Genetics, Molecular Biology

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In Genetics

1. David N. Cooper
2. Matthew E. Mort
3. Tom R. Gaunt
4. Hashem A. Shihab
5. Peter D. Stenson

In Molecular Biology

1. Matthew E. Mort
2. David N. Cooper
3. Colin Campbell
4. Tom R. Gaunt
5. Mark F. Rogers
6. Hashem A. Shihab

Citations in the corpus

• CADD: predicting the deleteriousness of variants throughout the human genome (2018, neutral): “However, for an alternative view on this topic, we refer the reader to recent methods that use CADD scores in conjunction with hard cutoffs; see GAVIN (23) and MSC (24).”
• ClinPred: Prediction Tool to Identify Disease-Relevant Nonsynonymous Single-Nucleotide Variants. (2018, background): “36 VVP incorporated population variant frequencies from the WGS portion of gnomAD (15,496 whole genomes) while we not only incorporate gnomAD all-exome AFs (123,136 exome sequences), but also AFs in 8 different populations available in gnomAD: African/ African American, Latino/Admixed American,…”
• FATHMM-XF: accurate prediction of pathogenic point mutations via extended features (2017, methodology): “GAVIN achieves higher MCC and PPV scores at the expense of lower accuracy.”