Multiple different evidence types as well as gene-specific variant classification guidelines need to be considered during the classification of variants, making the process complex. Therefore, tools that support variant classification by experts are urgently needed. We present HerediVar a web application and HerediClassify a variant classification algorithm. The performance of HerediClassify was validated and compared to other variant classification tools. HerediClassify implements 19/28 variant classification criteria by the American College of Medical Genetics and gene-specific recommendations for ATM, BRCA1, BRCA2, CDH1, PALB2, PTEN, and TP53. HerediVar offers modular annotation services and allows for collaboration in the classification of variants. On the validation dataset, HerediClassify shows an average F1-Score of 93% across all criteria. HerediClassify outperforms other automated variant classification tools like vaRHC and Cancer SIGVAR. In HerediVar and HerediClassify we present a powerful solution to support variant classification in HBOC. Through their modular design, HerediVar and HerediClassify are easily extendable to other use cases and human genetic diagnostics as a whole.
山东省济南市章丘区文博路2号
齐鲁师范学院 genelibs生信实验室
山东省济南市高新区舜华路750号
大学科技园北区F座4单元2楼
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