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Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application

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Review of applications of high-throughput sequencing in personalized medicine : barriers and facilitators of future progress in research and clinical application. / Lightbody, Gaye; Haberland, Valeriia; Browne, Fiona; Taggart, Laura; Zheng, Huiru; Parkes, Eileen; Blayney, Jaine K.

In: Briefings in Bioinformatics, 31.07.2018.

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Lightbody, Gaye ; Haberland, Valeriia ; Browne, Fiona ; Taggart, Laura ; Zheng, Huiru ; Parkes, Eileen ; Blayney, Jaine K. / Review of applications of high-throughput sequencing in personalized medicine : barriers and facilitators of future progress in research and clinical application. In: Briefings in Bioinformatics. 2018.

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@article{d134f3535c07492eb844734d3b89f599,
title = "Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application",
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. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), 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 article provides an up-to-date overview of the evolution of HTS 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 personalized medicine.",
keywords = "high-throughput sequencing, personalized medicine, clinical translation, translational research, high-performance computing, grid computing, cloud computing",
author = "Gaye Lightbody and Valeriia Haberland and Fiona Browne and Laura Taggart and Huiru Zheng and Eileen Parkes and Blayney, {Jaine K}",
year = "2018",
month = "7",
day = "31",
doi = "10.1093/bib/bby051",
language = "English",
journal = "Briefings in Bioinformatics",
issn = "1467-5463",
publisher = "Oxford University Press",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Review of applications of high-throughput sequencing in personalized medicine

T2 - barriers and facilitators of future progress in research and clinical application

AU - Lightbody, Gaye

AU - Haberland, Valeriia

AU - Browne, Fiona

AU - Taggart, Laura

AU - Zheng, Huiru

AU - Parkes, Eileen

AU - Blayney, Jaine K

PY - 2018/7/31

Y1 - 2018/7/31

N2 - 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. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), 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 article provides an up-to-date overview of the evolution of HTS 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 personalized medicine.

AB - 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. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), 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 article provides an up-to-date overview of the evolution of HTS 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 personalized medicine.

KW - high-throughput sequencing

KW - personalized medicine

KW - clinical translation

KW - translational research

KW - high-performance computing

KW - grid computing

KW - cloud computing

U2 - 10.1093/bib/bby051

DO - 10.1093/bib/bby051

M3 - Article

JO - Briefings in Bioinformatics

JF - Briefings in Bioinformatics

SN - 1467-5463

M1 - bby051

ER -