Review of Applications of High-Throughput Sequencing in Personalised Medicine: Barriers and Facilitators of Future Progress in Research and Clinical Application

G Lightbody, Valeriia Haberland, Browne Fiona, Laura Taggart, Huiru Zheng, Eileen Parks, Jaine Blayney

Research output: Contribution to journalReview article

12 Citations (Scopus)
55 Downloads (Pure)

Abstract

There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. This data may hold the promise of personalised medicine, leading to routinely-available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing, computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that
the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors including, sample sourcing, technology selection, and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems.
This paper provides an up-to-date overview of the evolution of high-throughput
sequencing and the accompanying tools, infrastructure and data management
approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalised medicine.
Original languageEnglish
Article numberbby051
Number of pages17
JournalBriefings in Bioinformatics
Early online date31 Jul 2018
DOIs
Publication statusE-pub ahead of print - 31 Jul 2018

Keywords

  • high-throughput sequencing
  • personalised medicine
  • clinical translation
  • translational research
  • high-performance computing
  • grid computing
  • cloud computing

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