Journal article
How to identify pathogenic mutations among all those variations: Variant annotation and filtration in the genome sequencing era
Human Mutation, Vol.37(12), pp.1272-1282
2016
Abstract
High-throughput sequencing technologies have become fundamental for the identification of disease-causing mutations in human genetic diseases both in research and clinical testing contexts. The cumulative number of genes linked to rare diseases is now close to 3,500 with more than 1,000 genes identified between 2010 and 2014 because of the early adoption of Exome Sequencing technologies. However, despite these encouraging figures, the success rate of clinical exome diagnosis remains low due to several factors including wrong variant annotation and nonoptimal filtration practices, which may lead to misinterpretation of disease-causing mutations. In this review, we describe the critical steps of variant annotation and filtration processes to highlight a handful of potential disease-causing mutations for downstream analysis. We report the key annotation elements to gather at multiple levels for each mutation, and which systems are designed to help in collecting this mandatory information. We describe the filtration options, their efficiency, and limits and provide a generic filtration workflow and highlight potential pitfalls through a use case.
Details
- Title
- How to identify pathogenic mutations among all those variations: Variant annotation and filtration in the genome sequencing era
- Authors/Creators
- D. Salgado (Author/Creator)M.I. Bellgard (Author/Creator)J-P Desvignes (Author/Creator)C. Beroud (Author/Creator)
- Publication Details
- Human Mutation, Vol.37(12), pp.1272-1282
- Publisher
- John Wiley & Sons Inc.
- Identifiers
- 991005540740207891
- Copyright
- © 2016 Wiley Periodicals, Inc.
- Murdoch Affiliation
- Centre for Comparative Genomics
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.189 Genome Studies
- 1.189.597 Genetic Testing
- Web Of Science research areas
- Genetics & Heredity
- ESI research areas
- Molecular Biology & Genetics