Simultaneous analysis of all single-nucleotide polymorphisms in genome-wide association study of rheumatoid arthritis.
| dc.contributor.author | Mathew, George | |
| dc.contributor.author | Xu, Hongyan | |
| dc.contributor.author | George, Varghese | |
| dc.date.accessioned | 2010-09-24T21:58:58Z | en |
| dc.date.available | 2010-09-24T21:58:58Z | en |
| dc.date.issued | 2009-12-18 | en_US |
| dc.identifier.citation | BMC Proc. 2009 Dec 15; 3(Suppl 7):S11 | en_US |
| dc.identifier.issn | 1753-6561 | en_US |
| dc.identifier.pmid | 20017974 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10675.2/87 | en |
| dc.description.abstract | ABSTRACT : The availability of very large number of markers by modern technology makes genome-wide association studies very popular. The usual approach is to test single-nucleotide polymorphisms (SNPs) one at a time for association with disease status. However, it may not be possible to detect marginally significant effects by single-SNP analysis. Simultaneous analysis of SNPs enables detection of even those SNPs with small effect by evaluating the collective impact of several neighboring SNPs. Also, false-positive signals may be weakened by the presence of other neighboring SNPs included in the analysis. We analyzed the North American Rheumatoid Arthritis Consortium data of Genetic Analysis Workshop 16 using HLasso, a new method for simultaneous analysis of SNPs. The simultaneous analysis approach has excellent control of type I error, and many of the previously reported results of single-SNP analyses were confirmed by this approach. | |
| dc.rights | The PMC Open Access Subset is a relatively small part of the total collection of articles in PMC. Articles in the PMC Open Access Subset are still protected by copyright, but are made available under a Creative Commons or similar license that generally allows more liberal redistribution and reuse than a traditional copyrighted work. Please refer to the license statement in each article for specific terms of use. The license terms are not identical for all articles in this subset. | en_US |
| dc.title | Simultaneous analysis of all single-nucleotide polymorphisms in genome-wide association study of rheumatoid arthritis. | en_US |
| dc.type | Journal Article | en_US |
| dc.identifier.pmcid | PMC2795881 | en_US |
| dc.contributor.corporatename | Department of Biostatistics and Epidemiology | en_US |
| refterms.dateFOA | 2019-04-10T00:59:35Z | |
| html.description.abstract | ABSTRACT : The availability of very large number of markers by modern technology makes genome-wide association studies very popular. The usual approach is to test single-nucleotide polymorphisms (SNPs) one at a time for association with disease status. However, it may not be possible to detect marginally significant effects by single-SNP analysis. Simultaneous analysis of SNPs enables detection of even those SNPs with small effect by evaluating the collective impact of several neighboring SNPs. Also, false-positive signals may be weakened by the presence of other neighboring SNPs included in the analysis. We analyzed the North American Rheumatoid Arthritis Consortium data of Genetic Analysis Workshop 16 using HLasso, a new method for simultaneous analysis of SNPs. The simultaneous analysis approach has excellent control of type I error, and many of the previously reported results of single-SNP analyses were confirmed by this approach. |
