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Selection of single-nucleotide polymorphisms in disease association data
We studied several methods for selecting single-nucleotide polymorphisms (SNPs) in a disease association study. Two major categories for analytical strategy are the univariate and the set selection approaches. The univariate approach evaluates each SNP marker one at a time, while the set selection a...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866686/ https://www.ncbi.nlm.nih.gov/pubmed/16451709 http://dx.doi.org/10.1186/1471-2156-6-S1-S93 |
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author | Joo, Jungnam Tian, Xin Zheng, Gang Lin, Jing-Ping Geller, Nancy L |
author_facet | Joo, Jungnam Tian, Xin Zheng, Gang Lin, Jing-Ping Geller, Nancy L |
author_sort | Joo, Jungnam |
collection | PubMed |
description | We studied several methods for selecting single-nucleotide polymorphisms (SNPs) in a disease association study. Two major categories for analytical strategy are the univariate and the set selection approaches. The univariate approach evaluates each SNP marker one at a time, while the set selection approach tests disease association of a set of SNP markers simultaneously. We examined various test statistics that can be utilized in testing disease association and also reviewed several multiple testing procedures that can properly control the family-wise error rates when the univariate approach is applied to multiple markers. The set association methods were then briefly reviewed. Finally, we applied these methods to the data from Collaborative Study on the Genetics of Alcoholism (COGA). |
format | Text |
id | pubmed-1866686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18666862007-05-11 Selection of single-nucleotide polymorphisms in disease association data Joo, Jungnam Tian, Xin Zheng, Gang Lin, Jing-Ping Geller, Nancy L BMC Genet Proceedings We studied several methods for selecting single-nucleotide polymorphisms (SNPs) in a disease association study. Two major categories for analytical strategy are the univariate and the set selection approaches. The univariate approach evaluates each SNP marker one at a time, while the set selection approach tests disease association of a set of SNP markers simultaneously. We examined various test statistics that can be utilized in testing disease association and also reviewed several multiple testing procedures that can properly control the family-wise error rates when the univariate approach is applied to multiple markers. The set association methods were then briefly reviewed. Finally, we applied these methods to the data from Collaborative Study on the Genetics of Alcoholism (COGA). BioMed Central 2005-12-30 /pmc/articles/PMC1866686/ /pubmed/16451709 http://dx.doi.org/10.1186/1471-2156-6-S1-S93 Text en Copyright © 2005 Joo 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 Joo, Jungnam Tian, Xin Zheng, Gang Lin, Jing-Ping Geller, Nancy L Selection of single-nucleotide polymorphisms in disease association data |
title | Selection of single-nucleotide polymorphisms in disease association data |
title_full | Selection of single-nucleotide polymorphisms in disease association data |
title_fullStr | Selection of single-nucleotide polymorphisms in disease association data |
title_full_unstemmed | Selection of single-nucleotide polymorphisms in disease association data |
title_short | Selection of single-nucleotide polymorphisms in disease association data |
title_sort | selection of single-nucleotide polymorphisms in disease association data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866686/ https://www.ncbi.nlm.nih.gov/pubmed/16451709 http://dx.doi.org/10.1186/1471-2156-6-S1-S93 |
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