The applications of big data in molecular diagnostics. (3rd October 2019)

• Record Type: Journal Article
• Authors: Wong, Yin Kwan Evelyn; Lam, Ka Wai; Ho, Ka Yi; Yu, Chi Shing Allen; Cho, Chi Shing William; Tsang, Hin Fung; Chu, Man Kee Maggie; Ng, Po Wah Lawrence; Tai, Chi Shing William; Chan, Lawrence Wing Chi; Wong, Elaine Yue Ling; Wong, Sze Chuen Cesar
• Is Part Of: Expert review of molecular diagnostics. Volume 19:Number 10(2019)
• Page Start: 905
• Page End: 917
• Publication Date: 2019-10-03
• Subjects: Big data -- bioinformatics -- molecular diagnostics -- application -- medical laboratory science -- training; Molecular diagnosis -- Periodicals; 616.0758205
• DOI: 10.1080/14737159.2019.1657834
• Languages: English
• ISSNs: 1473-7159

Abstract

ABSTRACT: Introduction : Big Data technologies instilled an informational perspective to our understanding of the world. However, fundamental issues such as the management and storage of data can create privacy concerns. Heterogeneous types of data pose challenges in reproducibility and standardization. It is now an opportunity for us to help the health-care professionals, educators, and policy-makers understand the impact of Big Data, and steer the development roadmap to positively impact the molecular diagnostic industry. Area covered : In this review, we discuss the latest trends in applying Big Data to several key areas of molecular diagnostics: metagenomics, Mendelian disease screening, personalized medicine, and metabolomics. The limitations of utilizing bioinformatics and Big Data analytic tools are also summarized. We further propose an action plan on how to prepare a new generation of health-care professionals to step into the age of Big Data through a tailor-made bioinformatics training program. Expert opinion : In order to cope with the development of these powerful technologies, issues of ethics, regulations, and data format standardization are urgently needed. Besides, a long-term planning to train medical scientists, pathologists, and specialists on bioinformatics is necessary. It is an appropriate time to review all these issues before implementing these tests for patients' diagnosis, prognosis and treatment efficacy.