| Literature DB >> 31623871 |
Zhichao Liu1, Liyuan Zhu2, Ruth Roberts3, Weida Tong4.
Abstract
Next-generation sequencing (NGS) technologies have changed the landscape of genetic testing in rare diseases. However, the rapid evolution of NGS technologies has outpaced its clinical adoption. Here, we re-evaluate the critical steps in the clinical application of NGS-based genetic testing from an informatics perspective. We suggest a 'fit-for-purpose' triage of current NGS technologies. We also point out potential shortcomings in the clinical management of genetic variants and offer ideas for potential improvement. We specifically emphasize the importance of ensuring the accuracy and reproducibility of NGS-based genetic testing in the context of rare disease diagnosis. We highlight the role of artificial intelligence (AI) in enhancing understanding and prioritization of variance in the clinical setting and propose deep learning frameworks for further investigation. Published by Elsevier Ltd.Keywords: artificial intelligence; clinical diagnosis; next-generation sequencing; rare diseases
Mesh:
Year: 2019 PMID: 31623871 DOI: 10.1016/j.tig.2019.08.006
Source DB: PubMed Journal: Trends Genet ISSN: 0168-9525 Impact factor: 11.639