| pubmed-article:18759969 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:18759969 | lifeskim:mentions | umls-concept:C0205419 | lld:lifeskim |
| pubmed-article:18759969 | lifeskim:mentions | umls-concept:C1710082 | lld:lifeskim |
| pubmed-article:18759969 | lifeskim:mentions | umls-concept:C1979874 | lld:lifeskim |
| pubmed-article:18759969 | lifeskim:mentions | umls-concept:C1552603 | lld:lifeskim |
| pubmed-article:18759969 | lifeskim:mentions | umls-concept:C1706202 | lld:lifeskim |
| pubmed-article:18759969 | lifeskim:mentions | umls-concept:C1511978 | lld:lifeskim |
| pubmed-article:18759969 | pubmed:dateCreated | 2008-9-30 | lld:pubmed |
| pubmed-article:18759969 | pubmed:abstractText | Genome-wide association (GWA) using large numbers of single nucleotide polymorphisms (SNPs) is now a powerful, state-of-the-art approach to mapping human disease genes. When a GWA study detects association between a SNP and the disease, this signal usually represents association with a set of several highly correlated SNPs in strong linkage disequilibrium. The challenge we address is to distinguish among these correlated loci to highlight potential functional variants and prioritize them for follow-up. | lld:pubmed |
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| pubmed-article:18759969 | pubmed:language | eng | lld:pubmed |
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| pubmed-article:18759969 | pubmed:citationSubset | IM | lld:pubmed |
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| pubmed-article:18759969 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:18759969 | pubmed:issn | 1471-2156 | lld:pubmed |
| pubmed-article:18759969 | pubmed:author | pubmed-author:BierutLaura... | lld:pubmed |
| pubmed-article:18759969 | pubmed:author | pubmed-author:RiceJohn PJP | lld:pubmed |
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| pubmed-article:18759969 | pubmed:author | pubmed-author:GruczaRichard... | lld:pubmed |
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| pubmed-article:18759969 | pubmed:author | pubmed-author:HinrichsAntho... | lld:pubmed |
| pubmed-article:18759969 | pubmed:author | pubmed-author:SacconeScott... | lld:pubmed |
| pubmed-article:18759969 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:18759969 | pubmed:volume | 9 | lld:pubmed |
| pubmed-article:18759969 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:18759969 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:18759969 | pubmed:pagination | 58 | lld:pubmed |
| pubmed-article:18759969 | pubmed:dateRevised | 2011-7-15 | lld:pubmed |
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| pubmed-article:18759969 | pubmed:year | 2008 | lld:pubmed |
| pubmed-article:18759969 | pubmed:articleTitle | In search of causal variants: refining disease association signals using cross-population contrasts. | lld:pubmed |
| pubmed-article:18759969 | pubmed:affiliation | Department of Genetics, Washington University, Campus Box 8232, 4566 Scott Avenue, Saint Louis, Missouri, USA. nlims@wustl.edu | lld:pubmed |
| pubmed-article:18759969 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:18759969 | pubmed:publicationType | Comparative Study | lld:pubmed |
| pubmed-article:18759969 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
| pubmed-article:18759969 | pubmed:publicationType | Multicenter Study | lld:pubmed |
| pubmed-article:18759969 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |
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