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Harnessing virtual machines to simplify next-generation DNA sequencing analysis.

Nocq J, Celton M, Gendron P, Lemieux S, Wilhelm BT

Institute for Research in Immunology and Cancer, University of Montreal, Laboratory for High-Throughput Genomics, Department of Medicine, University of Montreal, QC H3T 1J4, Canada, INRA, UMR1083, Sciences pour l'Oenologie, Montpellier, France and Laboratory for Functional and Structural Bioinformatics, Computer Sciences and Operation Research, University of Montreal, QC H3T 1J4, Canada.

The growth of next-generation sequencing (NGS) has not only dramatically accelerated the pace of research in the field of genomics, but it has also opened the door to personalized medicine and diagnostics. The resulting flood of data has led to the rapid development of large numbers of bioinformatic tools for data analysis, creating a challenging situation for researchers when choosing and configuring a variety of software for their analysis, and for other researchers trying to replicate their analysis. As NGS technology continues to expand from the research environment into clinical laboratories, the challenges associated with data analysis have the potential to slow the adoption of this technology.

Bioinformatics 2013;29(17):2075-83.

Pubmed ID: 23786767

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