Open AccessCloud-based genomics pipelines for ophthalmology: reviewed from research to clinical practice
Author(s) -
David Wong,
Maximiliano Olivera,
Jingjing Yu,
Anita Szabó,
Ismail Moghul,
Konstantinos Balaskas,
Robert Luben,
Anthony P. Khawaja,
Nikolas Pontikos,
Pearse A. Keane
Publication year - 2021
Publication title -
modeling and artificial intelligence in ophthalmology
Language(s) - English
Resource type - Journals
eISSN - 2772-9605
pISSN - 2772-9591
DOI - 10.35119/maio.v3i1.115
Subject(s) - cloud computing , genomics , data science , computer science , data sharing , scalability , medicine , pathology , genome , database , alternative medicine , biology , biochemistry , gene , operating system
Aim: To familiarize clinicians with clinical genomics, and to describe the potential of cloud computing for enabling the future routine use of genomics in eye hospital settings.Design: Review article exploring the potential for cloud-based genomic pipelines in eye hospitals.Methods: Narrative review of the literature relevant to clinical genomics and cloud computing, using PubMed and Google Scholar. A broad overview of these fields is provided, followed by key examples of their integration.Results: Cloud computing could benefit clinical genomics due to scalability of resources, potentially lower costs, and ease of data sharing between multiple institutions. Challenges include complex pricing of services, costs from mistakes or experimentation, data security, and privacy concerns.Conclusions and future perspectives: Clinical genomics is likely to become more routinely used in clinical practice. Currently this is delivered in highly specialist centers. In the future, cloud computing could enable delivery of clinical genomics services in non-specialist hospital settings, in a fast, cost-effective way, whilst enhancing collaboration between clinical and research teams.