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.
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 language | English |
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Article number | bby051 |
Number of pages | 17 |
Journal | Briefings in Bioinformatics |
Early online date | 31 Jul 2018 |
DOIs | |
Publication status | Published online - 31 Jul 2018 |
Keywords
- high-throughput sequencing
- personalised medicine
- clinical translation
- translational research
- high-performance computing
- grid computing
- cloud computing