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Memory management in genome-wide association studies
Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed mem...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795954/ https://www.ncbi.nlm.nih.gov/pubmed/20018047 |
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author | Chen, Xiang Zhang, Meizhuo Wang, Minghui Zhu, Wensheng Cho, Kelly Zhang, Heping |
author_facet | Chen, Xiang Zhang, Meizhuo Wang, Minghui Zhu, Wensheng Cho, Kelly Zhang, Heping |
author_sort | Chen, Xiang |
collection | PubMed |
description | Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies. |
format | Text |
id | pubmed-2795954 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27959542009-12-18 Memory management in genome-wide association studies Chen, Xiang Zhang, Meizhuo Wang, Minghui Zhu, Wensheng Cho, Kelly Zhang, Heping BMC Proc Proceedings Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies. BioMed Central 2009-12-15 /pmc/articles/PMC2795954/ /pubmed/20018047 Text en Copyright ©2009 Chen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Chen, Xiang Zhang, Meizhuo Wang, Minghui Zhu, Wensheng Cho, Kelly Zhang, Heping Memory management in genome-wide association studies |
title | Memory management in genome-wide association studies |
title_full | Memory management in genome-wide association studies |
title_fullStr | Memory management in genome-wide association studies |
title_full_unstemmed | Memory management in genome-wide association studies |
title_short | Memory management in genome-wide association studies |
title_sort | memory management in genome-wide association studies |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795954/ https://www.ncbi.nlm.nih.gov/pubmed/20018047 |
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