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Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Seoae | - |
dc.contributor.author | Kim, Haseong | - |
dc.contributor.author | Oh, Sohee | - |
dc.contributor.author | Kim, Kyunga | - |
dc.contributor.author | Park, Taesung | - |
dc.date.accessioned | 2017-03-27T00:51:45Z | - |
dc.date.available | 2017-03-27T09:56:47Z | - |
dc.date.issued | 2009-12-15 | - |
dc.identifier.citation | BMC Proceedings, 3(Suppl 7):S25 | ko_KR |
dc.identifier.uri | https://hdl.handle.net/10371/109988 | - |
dc.description.abstract | The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility. | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BioMed Central | ko_KR |
dc.title | Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 조서애 | - |
dc.contributor.AlternativeAuthor | 김하성 | - |
dc.contributor.AlternativeAuthor | 오소희 | - |
dc.contributor.AlternativeAuthor | 김경아 | - |
dc.contributor.AlternativeAuthor | 박태성 | - |
dc.identifier.doi | 10.1186/1753-6561-3-S7-S25 | - |
dc.language.rfc3066 | en | - |
dc.rights.holder | Cho et al; licensee BioMed Central Ltd. | - |
dc.date.updated | 2017-01-06T10:52:20Z | - |
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