GAVIN: Gene-Aware Variant INterpretation for medical sequencing
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- 作者：K. Joeri van der Velde ; Eddy N. de Boer ; Cleo C. van Diemen…
- 关键词：Clinical next ; generation sequencing ; Variant classification ; Automated protocol ; Gene ; specific calibration ; Allele frequency ; Protein impact ; Pathogenicity prediction
- 刊名：Genome Biology
- 出版年：2017
- 出版时间：December 2017
- 年：2017
- 卷：18
- 期：1
- 全文大小：1108KB
- 刊物主题：Animal Genetics and Genomics; Human Genetics; Plant Genetics & Genomics; Microbial Genetics and Genomics; Bioinformatics; Evolutionary Biology;
- 出版者：BioMed Central
- ISSN：1474-760X
- 卷排序：18
文摘
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.