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OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid

High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challeng...

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Detalles Bibliográficos
Autores principales: Poehlman, William L., Rynge, Mats, Branton, Chris, Balamurugan, D., Feltus, Frank A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4972127/
https://www.ncbi.nlm.nih.gov/pubmed/27499617
http://dx.doi.org/10.4137/BBI.S38193
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author Poehlman, William L.
Rynge, Mats
Branton, Chris
Balamurugan, D.
Feltus, Frank A.
author_facet Poehlman, William L.
Rynge, Mats
Branton, Chris
Balamurugan, D.
Feltus, Frank A.
author_sort Poehlman, William L.
collection PubMed
description High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments.
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spelling pubmed-49721272016-08-05 OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid Poehlman, William L. Rynge, Mats Branton, Chris Balamurugan, D. Feltus, Frank A. Bioinform Biol Insights Technical Advance High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments. Libertas Academica 2016-08-02 /pmc/articles/PMC4972127/ /pubmed/27499617 http://dx.doi.org/10.4137/BBI.S38193 Text en © 2016 the author(s), publisher and licensee Libertas Academica Ltd. This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 License.
spellingShingle Technical Advance
Poehlman, William L.
Rynge, Mats
Branton, Chris
Balamurugan, D.
Feltus, Frank A.
OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
title OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
title_full OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
title_fullStr OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
title_full_unstemmed OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
title_short OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
title_sort osg-gem: gene expression matrix construction using the open science grid
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4972127/
https://www.ncbi.nlm.nih.gov/pubmed/27499617
http://dx.doi.org/10.4137/BBI.S38193
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