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OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid
Author(s) -
William L. Poehlman,
Mats Rynge,
Chris Branton,
D. Balamurugan,
F. Alex Feltus
Publication year - 2016
Publication title -
bioinformatics and biology insights
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 23
ISSN - 1177-9322
DOI - 10.4137/bbi.s38193
Subject(s) - workflow , computer science , scalability , grid , workflow management system , throughput , grid computing , dna sequencing , distributed computing , software engineering , computational biology , data mining , database , operating system , gene , biology , biochemistry , geometry , mathematics , wireless
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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