Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows

While Next-Generation Sequencing (NGS) can now be considered an established analysis technology for research applications across the life sciences, the analysis workflows still require substantial bioinformatics expertise. Typical challenges include the appropriate selection of analytical software t...

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Main Authors: Pranav Kulkarni, Peter Frommolt
Format: Article
Language:English
Published: Elsevier 2017-01-01
Series:Computational and Structural Biotechnology Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037017300776
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spelling doaj-40e88d69008b443abd1ec094106b2f122020-11-25T01:06:46ZengElsevierComputational and Structural Biotechnology Journal2001-03702017-01-0115471477Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis WorkflowsPranav Kulkarni0Peter Frommolt1Bioinformatics Core Facility, CECAD Research Center, University of Cologne, GermanyCorresponding author.; Bioinformatics Core Facility, CECAD Research Center, University of Cologne, GermanyWhile Next-Generation Sequencing (NGS) can now be considered an established analysis technology for research applications across the life sciences, the analysis workflows still require substantial bioinformatics expertise. Typical challenges include the appropriate selection of analytical software tools, the speedup of the overall procedure using HPC parallelization and acceleration technology, the development of automation strategies, data storage solutions and finally the development of methods for full exploitation of the analysis results across multiple experimental conditions. Recently, NGS has begun to expand into clinical environments, where it facilitates diagnostics enabling personalized therapeutic approaches, but is also accompanied by new technological, legal and ethical challenges. There are probably as many overall concepts for the analysis of the data as there are academic research institutions. Among these concepts are, for instance, complex IT architectures developed in-house, ready-to-use technologies installed on-site as well as comprehensive Everything as a Service (XaaS) solutions. In this mini-review, we summarize the key points to consider in the setup of the analysis architectures, mostly for scientific rather than diagnostic purposes, and provide an overview of the current state of the art and challenges of the field.http://www.sciencedirect.com/science/article/pii/S2001037017300776
collection DOAJ
language English
format Article
sources DOAJ
author Pranav Kulkarni
Peter Frommolt
spellingShingle Pranav Kulkarni
Peter Frommolt
Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows
Computational and Structural Biotechnology Journal
author_facet Pranav Kulkarni
Peter Frommolt
author_sort Pranav Kulkarni
title Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows
title_short Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows
title_full Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows
title_fullStr Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows
title_full_unstemmed Challenges in the Setup of Large-scale Next-Generation Sequencing Analysis Workflows
title_sort challenges in the setup of large-scale next-generation sequencing analysis workflows
publisher Elsevier
series Computational and Structural Biotechnology Journal
issn 2001-0370
publishDate 2017-01-01
description While Next-Generation Sequencing (NGS) can now be considered an established analysis technology for research applications across the life sciences, the analysis workflows still require substantial bioinformatics expertise. Typical challenges include the appropriate selection of analytical software tools, the speedup of the overall procedure using HPC parallelization and acceleration technology, the development of automation strategies, data storage solutions and finally the development of methods for full exploitation of the analysis results across multiple experimental conditions. Recently, NGS has begun to expand into clinical environments, where it facilitates diagnostics enabling personalized therapeutic approaches, but is also accompanied by new technological, legal and ethical challenges. There are probably as many overall concepts for the analysis of the data as there are academic research institutions. Among these concepts are, for instance, complex IT architectures developed in-house, ready-to-use technologies installed on-site as well as comprehensive Everything as a Service (XaaS) solutions. In this mini-review, we summarize the key points to consider in the setup of the analysis architectures, mostly for scientific rather than diagnostic purposes, and provide an overview of the current state of the art and challenges of the field.
url http://www.sciencedirect.com/science/article/pii/S2001037017300776
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