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Genome Modeling System: A Knowledge Management Platform for Genomics
In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines....
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4497734/ https://www.ncbi.nlm.nih.gov/pubmed/26158448 http://dx.doi.org/10.1371/journal.pcbi.1004274 |
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author | Griffith, Malachi Griffith, Obi L. Smith, Scott M. Ramu, Avinash Callaway, Matthew B. Brummett, Anthony M. Kiwala, Michael J. Coffman, Adam C. Regier, Allison A. Oberkfell, Ben J. Sanderson, Gabriel E. Mooney, Thomas P. Nutter, Nathaniel G. Belter, Edward A. Du, Feiyu Long, Robert L. Abbott, Travis E. Ferguson, Ian T. Morton, David L. Burnett, Mark M. Weible, James V. Peck, Joshua B. Dukes, Adam McMichael, Joshua F. Lolofie, Justin T. Derickson, Brian R. Hundal, Jasreet Skidmore, Zachary L. Ainscough, Benjamin J. Dees, Nathan D. Schierding, William S. Kandoth, Cyriac Kim, Kyung H. Lu, Charles Harris, Christopher C. Maher, Nicole Maher, Christopher A. Magrini, Vincent J. Abbott, Benjamin S. Chen, Ken Clark, Eric Das, Indraniel Fan, Xian Hawkins, Amy E. Hepler, Todd G. Wylie, Todd N. Leonard, Shawn M. Schroeder, William E. Shi, Xiaoqi Carmichael, Lynn K. Weil, Matthew R. Wohlstadter, Richard W. Stiehr, Gary McLellan, Michael D. Pohl, Craig S. Miller, Christopher A. Koboldt, Daniel C. Walker, Jason R. Eldred, James M. Larson, David E. Dooling, David J. Ding, Li Mardis, Elaine R. Wilson, Richard K. |
author_facet | Griffith, Malachi Griffith, Obi L. Smith, Scott M. Ramu, Avinash Callaway, Matthew B. Brummett, Anthony M. Kiwala, Michael J. Coffman, Adam C. Regier, Allison A. Oberkfell, Ben J. Sanderson, Gabriel E. Mooney, Thomas P. Nutter, Nathaniel G. Belter, Edward A. Du, Feiyu Long, Robert L. Abbott, Travis E. Ferguson, Ian T. Morton, David L. Burnett, Mark M. Weible, James V. Peck, Joshua B. Dukes, Adam McMichael, Joshua F. Lolofie, Justin T. Derickson, Brian R. Hundal, Jasreet Skidmore, Zachary L. Ainscough, Benjamin J. Dees, Nathan D. Schierding, William S. Kandoth, Cyriac Kim, Kyung H. Lu, Charles Harris, Christopher C. Maher, Nicole Maher, Christopher A. Magrini, Vincent J. Abbott, Benjamin S. Chen, Ken Clark, Eric Das, Indraniel Fan, Xian Hawkins, Amy E. Hepler, Todd G. Wylie, Todd N. Leonard, Shawn M. Schroeder, William E. Shi, Xiaoqi Carmichael, Lynn K. Weil, Matthew R. Wohlstadter, Richard W. Stiehr, Gary McLellan, Michael D. Pohl, Craig S. Miller, Christopher A. Koboldt, Daniel C. Walker, Jason R. Eldred, James M. Larson, David E. Dooling, David J. Ding, Li Mardis, Elaine R. Wilson, Richard K. |
author_sort | Griffith, Malachi |
collection | PubMed |
description | In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms. |
format | Online Article Text |
id | pubmed-4497734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44977342015-07-14 Genome Modeling System: A Knowledge Management Platform for Genomics Griffith, Malachi Griffith, Obi L. Smith, Scott M. Ramu, Avinash Callaway, Matthew B. Brummett, Anthony M. Kiwala, Michael J. Coffman, Adam C. Regier, Allison A. Oberkfell, Ben J. Sanderson, Gabriel E. Mooney, Thomas P. Nutter, Nathaniel G. Belter, Edward A. Du, Feiyu Long, Robert L. Abbott, Travis E. Ferguson, Ian T. Morton, David L. Burnett, Mark M. Weible, James V. Peck, Joshua B. Dukes, Adam McMichael, Joshua F. Lolofie, Justin T. Derickson, Brian R. Hundal, Jasreet Skidmore, Zachary L. Ainscough, Benjamin J. Dees, Nathan D. Schierding, William S. Kandoth, Cyriac Kim, Kyung H. Lu, Charles Harris, Christopher C. Maher, Nicole Maher, Christopher A. Magrini, Vincent J. Abbott, Benjamin S. Chen, Ken Clark, Eric Das, Indraniel Fan, Xian Hawkins, Amy E. Hepler, Todd G. Wylie, Todd N. Leonard, Shawn M. Schroeder, William E. Shi, Xiaoqi Carmichael, Lynn K. Weil, Matthew R. Wohlstadter, Richard W. Stiehr, Gary McLellan, Michael D. Pohl, Craig S. Miller, Christopher A. Koboldt, Daniel C. Walker, Jason R. Eldred, James M. Larson, David E. Dooling, David J. Ding, Li Mardis, Elaine R. Wilson, Richard K. PLoS Comput Biol Research Article In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms. Public Library of Science 2015-07-09 /pmc/articles/PMC4497734/ /pubmed/26158448 http://dx.doi.org/10.1371/journal.pcbi.1004274 Text en © 2015 Griffith et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Griffith, Malachi Griffith, Obi L. Smith, Scott M. Ramu, Avinash Callaway, Matthew B. Brummett, Anthony M. Kiwala, Michael J. Coffman, Adam C. Regier, Allison A. Oberkfell, Ben J. Sanderson, Gabriel E. Mooney, Thomas P. Nutter, Nathaniel G. Belter, Edward A. Du, Feiyu Long, Robert L. Abbott, Travis E. Ferguson, Ian T. Morton, David L. Burnett, Mark M. Weible, James V. Peck, Joshua B. Dukes, Adam McMichael, Joshua F. Lolofie, Justin T. Derickson, Brian R. Hundal, Jasreet Skidmore, Zachary L. Ainscough, Benjamin J. Dees, Nathan D. Schierding, William S. Kandoth, Cyriac Kim, Kyung H. Lu, Charles Harris, Christopher C. Maher, Nicole Maher, Christopher A. Magrini, Vincent J. Abbott, Benjamin S. Chen, Ken Clark, Eric Das, Indraniel Fan, Xian Hawkins, Amy E. Hepler, Todd G. Wylie, Todd N. Leonard, Shawn M. Schroeder, William E. Shi, Xiaoqi Carmichael, Lynn K. Weil, Matthew R. Wohlstadter, Richard W. Stiehr, Gary McLellan, Michael D. Pohl, Craig S. Miller, Christopher A. Koboldt, Daniel C. Walker, Jason R. Eldred, James M. Larson, David E. Dooling, David J. Ding, Li Mardis, Elaine R. Wilson, Richard K. Genome Modeling System: A Knowledge Management Platform for Genomics |
title | Genome Modeling System: A Knowledge Management Platform for Genomics |
title_full | Genome Modeling System: A Knowledge Management Platform for Genomics |
title_fullStr | Genome Modeling System: A Knowledge Management Platform for Genomics |
title_full_unstemmed | Genome Modeling System: A Knowledge Management Platform for Genomics |
title_short | Genome Modeling System: A Knowledge Management Platform for Genomics |
title_sort | genome modeling system: a knowledge management platform for genomics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4497734/ https://www.ncbi.nlm.nih.gov/pubmed/26158448 http://dx.doi.org/10.1371/journal.pcbi.1004274 |
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