| pubmed-article:19924712 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C1257890 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C2350277 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C0242262 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C0796344 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C0679199 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C1706244 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C0936012 | lld:lifeskim |
| pubmed-article:19924712 | lifeskim:mentions | umls-concept:C1880177 | lld:lifeskim |
| pubmed-article:19924712 | pubmed:dateCreated | 2009-11-30 | lld:pubmed |
| pubmed-article:19924712 | pubmed:abstractText | This contribution summarizes the work done by six independent teams of investigators to identify the genetic and non-genetic variants that work together or independently to predispose to disease. The theme addressed in these studies is multistage strategies in the context of genome-wide association studies (GWAS). The work performed comes from Group 3 of the Genetic Analysis Workshop 16 held in St. Louis, Missouri in September 2008. These six studies represent a diversity of multistage methods of which five are applied to the North American Rheumatoid Arthritis Consortium rheumatoid arthritis case-control data, and one method is applied to the low-density lipoprotein phenotype in the Framingham Heart Study simulated data. In the first stage of analyses, the majority of studies used a variety of screening techniques to reduce the noise of single-nucleotide polymorphisms purportedly not involved in the phenotype of interest. Three studies analyzed the data using penalized regression models, either LASSO or the elastic net. The main result was a reconfirmation of the involvement of variants in the HLA region on chromosome 6 with rheumatoid arthritis. The hope is that the intense computational methods highlighted in this group of papers will become useful tools in future GWAS. | lld:pubmed |
| pubmed-article:19924712 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19924712 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19924712 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19924712 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19924712 | pubmed:language | eng | lld:pubmed |
| pubmed-article:19924712 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19924712 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:19924712 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19924712 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:19924712 | pubmed:issn | 1098-2272 | lld:pubmed |
| pubmed-article:19924712 | pubmed:author | pubmed-author:NeumanRosalin... | lld:pubmed |
| pubmed-article:19924712 | pubmed:author | pubmed-author:SungYun JuYJ | lld:pubmed |
| pubmed-article:19924712 | pubmed:copyrightInfo | (c) 2009 Wiley-Liss, Inc. | lld:pubmed |
| pubmed-article:19924712 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:19924712 | pubmed:volume | 33 Suppl 1 | lld:pubmed |
| pubmed-article:19924712 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:19924712 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:19924712 | pubmed:pagination | S19-23 | lld:pubmed |
| pubmed-article:19924712 | pubmed:dateRevised | 2011-9-26 | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:meshHeading | pubmed-meshheading:19924712... | lld:pubmed |
| pubmed-article:19924712 | pubmed:year | 2009 | lld:pubmed |
| pubmed-article:19924712 | pubmed:articleTitle | Multistage analysis strategies for genome-wide association studies: summary of group 3 contributions to Genetic Analysis Workshop 16. | lld:pubmed |
| pubmed-article:19924712 | pubmed:affiliation | Department of Psychiatry, Washington University Medical School, St. Louis, Missouri 63108, USA. rneuman@wustl.edu | lld:pubmed |
| pubmed-article:19924712 | pubmed:publicationType | Congresses | lld:pubmed |
| pubmed-article:19924712 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |
