期刊
HUMAN MUTATION
卷 43, 期 5, 页码 539-546出版社
WILEY-HINDAWI
DOI: 10.1002/humu.24362
关键词
dbNSFP; disease; human phenotype ontology; phenotype; variant prioritization
资金
- McCusker Charitable Foundation
- Stan Perron Charitable Foundation
- Feilman Foundation
Identifying causal variants for genetic disease diagnosis is challenging, and variant prioritization tools can assist in this task. Our study found that these tools show differences in performance across different disease contexts, and we recommend three standout tools.
Identifying the causal variant for diagnosis of genetic diseases is challenging when using next-generation sequencing approaches and variant prioritization tools can assist in this task. These tools provide in silico predictions of variant pathogenicity, however they are agnostic to the disease under study. We previously performed a disease-specific benchmark of 24 such tools to assess how they perform in different disease contexts. We found that the tools themselves show large differences in performance, but more importantly that the best tools for variant prioritization are dependent on the disease phenotypes being considered. Here we expand the assessment to 37 tools and refine our assessment by separating performance for nonsynonymous single nucleotide variants (nsSNVs) and missense variants (i.e., excluding nonsense variants). We found differences in performance for missense variants compared to nsSNVs and recommend three tools that stand out in terms of their performance (BayesDel, CADD, and ClinPred).
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