Author:
Di Sera Tonya,Velinder Matt,Ward Alistair,Qiao Yi,Georges Stephanie,Miller Chase,Pitman Anders,Richards Will,Ekawade Aditya,Viskochil David,Carey John C.,Pace Laura,Bale Jim,Clardy Stacey L.,Andrews Ashley,Botto Lorenzo,Marth Gabor
Abstract
AbstractWith increasing utilization of comprehensive genomic data to guide clinical care, anticipated to become the standard of care in many clinical settings, the practice of diagnostic medicine is undergoing a notable shift. However, the move from single-gene or panel-based genetic testing to exome and genome sequencing has not been matched by the development of tools to enable diagnosticians to interpret increasingly complex or uncertain genomic findings. Here, we present gene.iobio, a real-time, intuitive and interactive web application for clinically-driven variant interrogation and prioritization. We show gene.iobio is a novel and effective approach that significantly improves upon and reimagines existing methods. In a radical departure from existing methods that present variants and genomic data in text and table formats, gene.iobio provides an interactive, intuitive and visually-driven analysis environment. We demonstrate that adoption of gene.iobio in clinical and research settings empowers clinical care providers to interact directly with patient genomic data both for establishing clinical diagnoses and informing patient care, using sophisticated genomic analyses that previously were only accessible via complex command line tools.
Funder
National Human Genome Research Institute
Publisher
Springer Science and Business Media LLC
Reference47 articles.
1. Paila, U., Chapman, B. A., Kirchner, R. & Quinlan, A. R. GEMINI: Integrative exploration of genetic variation and genome annotations. PLoS Comput. Biol. 9, e1003153 (2013).
2. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucl. Acids Res. 38, e164 (2010).
3. Moore, B., Flygare, S., Reese, M. G. & Yandell, M. VAAST 2.0: Improved variant classification and disease-gene identification using a conservation-controlled amino acid substitution matrix. Genetic 37, 622–634 (2013).
4. Pedersen, B. S. et al. Effective variant filtering and expected candidate variant yield in studies of rare human disease. NPJ Genom. Med. https://doi.org/10.1101/2020.08.13.249532 (2020).
5. Farnaes, L. et al. Rapid whole-genome sequencing decreases infant morbidity and cost of hospitalization. NPJ Genom. Med. 3, 10 (2018).
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