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dc.contributor.author Wu, Le-Shin
dc.contributor.author Ganote, Carrie
dc.contributor.author Doak, Thomas
dc.contributor.author Barnett, William K.
dc.contributor.author Mockaitis, Keithanne
dc.contributor.author Stewart, Craig A.
dc.date.accessioned 2015-11-11T18:37:25Z
dc.date.available 2015-11-11T18:37:25Z
dc.date.issued 2015-07-26
dc.identifier.citation Le-Shin Wu, Carrie L. Ganote, Thomas G. Doak, William Barnett, Keithanne Mockaitis, and Craig A. Stewart. 2015. Cyberinfrastructure resources enabling creation of the loblolly pine reference transcriptome. In Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure (XSEDE '15). ACM, New York, NY, USA. DOI=http://dx.doi.org/10.1145/2792745.2792748 en
dc.identifier.uri https://hdl.handle.net/2022/20488
dc.description This paper was presented at XSEDE 15 conference. en
dc.description.abstract Today's genomics technologies generate more sequence data than ever before possible, and at substantially lower costs, serving researchers across biological disciplines in transformative ways. Building transcriptome assemblies from RNA sequencing reads is one application of next-generation sequencing (NGS) that has held a central role in biological discovery in both model and non- model organisms, with and without whole genome sequence references. A major limitation in effective building of transcriptome references is no longer the sequencing data generation itself, but the computing infrastructure and expertise needed to assemble, analyze and manage the data. Here we describe a currently available resource dedicated to achieving such goals, and its use for extensive RNA assembly of up to 1.3 billion reads representing the massive transcriptome of loblolly pine, using four major assembly software installations. The Mason cluster, an XSEDE second tier resource at Indiana University, provides the necessary fast CPU cycles, large memory, and high I/O throughput for conducting large-scale genomics research. The National Center for Genome Analysis Support, or NCGAS, provides technical support in using HPC systems, bioinformatic support for determining the appropriate method to analyze a given dataset, and practical assistance in running computations. We demonstrate that a sufficient supercomputing resource and good workflow design are elements that are essential to large eukaryotic genomics and transcriptomics projects such as the complex transcriptome of loblolly pine, gene expression data that inform annotation and functional interpretation of the largest genome sequence reference to date. en
dc.description.sponsorship This work was supported in part by USDA NIFA grant 2011- 67009-30030, PineRefSeq, led by the University of California, Davis, and NCGAS funded by NSF under award No. 1062432. en
dc.language.iso en_US en
dc.publisher ACM, New York, NY en
dc.relation.isversionof http://dl.acm.org/citation.cfm?id=2792748 en
dc.rights Except where otherwise noted, the contents of this presentation are copyright of the Trustees of Indiana University. This content is released under the Creative Commons Attribution 3.0 Unported license (http://creativecommons.org/licenses/by/3.0/). This license includes the following terms: You are free to share - to copy, distribute and transmit the work and to remix - to adapt the work under the following conditions: attribution - you must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). For any reuse or distribution, you must make clear to others the license terms of this work en
dc.rights.uri http://creativecommons.org/licenses/by/3.0/ en
dc.subject NCGAS, Bioinformatics, Genome Analysis, Transcriptome, Sequence Assembly, Pine, large memory, Conifer, HPC en
dc.title Cyberinfrastructure resources enabling creation of the loblolly pine reference transcriptome en
dc.type Article en
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