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From Sequencer to Supercomputer: An Automatic Pipeline for Managing and Processing Next Generation Sequencing Data

Next Generation Sequencing is highly resource intensive. NGS Tasks related to data processing, management and analysis require high-end computing servers or even clusters. Additionally, processing NGS experiments requires suitable storage space and significant manual interaction. At The Ohio State U...

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Detalles Bibliográficos
Autores principales: Camerlengo, Terry, Ozer, Hatice Gulcin, Onti-Srinivasan, Raghuram, Yan, Pearlly, Huang, Tim, Parvin, Jeffrey, Huang, Kun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392054/
https://www.ncbi.nlm.nih.gov/pubmed/22779037
Descripción
Sumario:Next Generation Sequencing is highly resource intensive. NGS Tasks related to data processing, management and analysis require high-end computing servers or even clusters. Additionally, processing NGS experiments requires suitable storage space and significant manual interaction. At The Ohio State University's Biomedical Informatics Shared Resource, we designed and implemented a scalable architecture to address the challenges associated with the resource intensive nature of NGS secondary analysis built around Illumina Genome Analyzer II sequencers and Illumina’s Gerald data processing pipeline. The software infrastructure includes a distributed computing platform consisting of a LIMS called QUEST (http://bisr.osumc.edu), an Automation Server, a computer cluster for processing NGS pipelines, and a network attached storage device expandable up to 40TB. The system has been architected to scale to multiple sequencers without requiring additional computing or labor resources. This platform provides demonstrates how to manage and automate NGS experiments in an institutional or core facility setting.