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AVI Workshop on Big Data Applications

AVI-BDA 2016: Advanced Visual Interfaces. Supporting Big Data Applications pp 50–62Cite as

Visualizing Next-Generation Sequencing Cancer Data Sets with Cloud Computing

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10084))

Abstract

With the advent of next-generation sequencing technology, clinical data sets now contain enormous amounts of valuable genomic information related to a wide range of diseases such as cancer. This data needs to be analysed, managed, stored, visualized and integrated in order to be clinically useful. However, many clinicians and researchers, who need to interpret these data sets, are non-specialists in the information technology domain and so need systems that are effective and easy to use. Herein, we present an overview of a novel cloud computing based next-generation sequencing research management software system which has simplicity, scalability, speed and reproducibility at its core. A prototype that enables rapid visualization of big data cancer sets is described. We present preliminary results from a bioinformatics pipeline for the Sage Care project, a European Union funded cancer research project, for comprehensive genome mapping analysis and visualization and outlined benefits of integrating this into a graphical user interface platform such as Simplicity.

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Notes

  1. 1.

    Simplicity is a trademark NSilico Lifescience Ltd.

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Acknowledgements

Paul Walsh, Brian Kelly, Timm Heuss and Brendan Lawlor are investigators on Sage Care, a H2020 MCSA funded project, grant number 644186.

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Authors and Affiliations

  1. NSilico Lifescience, Rubicon Centre, CIT Campus, Bishopstown, Cork, Ireland

    Paul Walsh, Brendan Lawlor, Brian Kelly & Timmy Manning

  2. University of Applied Sciences Darmstadt, Darmstadt, Germany

    Timm Heuss & Markus Leopold

Authors
  1. Paul Walsh
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  2. Brendan Lawlor
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  3. Brian Kelly
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  4. Timmy Manning
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  5. Timm Heuss
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  6. Markus Leopold
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Corresponding author

Correspondence to Paul Walsh .

Editor information

Editors and Affiliations

  1. Faculty of Mathematics and Computer Science, University of Hagen, Hagen, Germany

    Marco X. Bornschlegl

  2. Faculty of Mathematics and Computer Science, University of Hagen, Hagen, Germany

    Felix C. Engel

  3. School of Computing and Mathematics, University of Ulster, Newtownabbey, Antrim, UK

    Raymond Bond

  4. Faculty of Mathematics and Computer Science, University of Hagen, Hagen, Germany

    Matthias L. Hemmje

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© 2016 Springer International Publishing AG

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Walsh, P., Lawlor, B., Kelly, B., Manning, T., Heuss, T., Leopold, M. (2016). Visualizing Next-Generation Sequencing Cancer Data Sets with Cloud Computing. In: Bornschlegl, M.X., Engel, F.C., Bond, R., Hemmje, M.L. (eds) Advanced Visual Interfaces. Supporting Big Data Applications. AVI-BDA 2016. Lecture Notes in Computer Science(), vol 10084. Springer, Cham. https://doi.org/10.1007/978-3-319-50070-6_4

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  • DOI: https://doi.org/10.1007/978-3-319-50070-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50069-0

  • Online ISBN: 978-3-319-50070-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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