| pubmed-article:15287819 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:15287819 | lifeskim:mentions | umls-concept:C0023746 | lld:lifeskim |
| pubmed-article:15287819 | lifeskim:mentions | umls-concept:C0018591 | lld:lifeskim |
| pubmed-article:15287819 | lifeskim:mentions | umls-concept:C0024779 | lld:lifeskim |
| pubmed-article:15287819 | pubmed:issue | 4 | lld:pubmed |
| pubmed-article:15287819 | pubmed:dateCreated | 2004-8-3 | lld:pubmed |
| pubmed-article:15287819 | pubmed:abstractText | There is currently a broad effort to produce genome-wide high-density linkage disequilibrium (LD) maps with single nucleotide polymorphisms. The hope is that the resulting maps can be exploited to find genes that affect the onset and severity of at least some common human diseases. These maps may also be useful for identifying genes that affect drug response or the likelihood of drug toxicities. The goal of this review is to provide a broad overview of some of the key concerns motivating the design of a major international project called the International Haplotype Map Project. The process of map production requires the identification of very large numbers of polymorphic sites, implementation of facile, highly accurate and inexpensive genotyping production pipelines, and provision for public access to the genotype data. Great progress has been made recently in genotyping methods and these advances are allowing very large-scale data collection. A major goal of these efforts is to enable the selection of subsets of markers that capture useful genetic information in short genomic intervals, while optimally reducing the number of markers that must be genotyped. Standard measures of LD provide a starting point but may not fully capture the complexity of the information inherent in the data. Extremely dense genotype data in several broadly representative populations (European, Chinese, Japanese, and Yoruba) should yield important insights into the genetic structure of most genes. Further study is required to determine how broadly applicable the data will be to other population groups. Significant challenges lie ahead in determining the best methods for the selection of markers in disease/phenotype studies, large-scale genotyping, and analysis of the resulting genetic data. | lld:pubmed |
| pubmed-article:15287819 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15287819 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15287819 | pubmed:language | eng | lld:pubmed |
| pubmed-article:15287819 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15287819 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:15287819 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15287819 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:15287819 | pubmed:issn | 1175-2203 | lld:pubmed |
| pubmed-article:15287819 | pubmed:author | pubmed-author:GibbsRichard... | lld:pubmed |
| pubmed-article:15287819 | pubmed:author | pubmed-author:BelmontJohn... | lld:pubmed |
| pubmed-article:15287819 | pubmed:copyrightInfo | Copyright 2004 Adis Data Information BV | lld:pubmed |
| pubmed-article:15287819 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:15287819 | pubmed:volume | 4 | lld:pubmed |
| pubmed-article:15287819 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:15287819 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:15287819 | pubmed:pagination | 253-62 | lld:pubmed |
| pubmed-article:15287819 | pubmed:dateRevised | 2007-11-14 | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:meshHeading | pubmed-meshheading:15287819... | lld:pubmed |
| pubmed-article:15287819 | pubmed:year | 2004 | lld:pubmed |
| pubmed-article:15287819 | pubmed:articleTitle | Genome-wide linkage disequilibrium and haplotype maps. | lld:pubmed |
| pubmed-article:15287819 | pubmed:affiliation | Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA. | lld:pubmed |
| pubmed-article:15287819 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:15287819 | pubmed:publicationType | Research Support, U.S. Gov't, P.H.S. | lld:pubmed |
| pubmed-article:15287819 | pubmed:publicationType | Review | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:15287819 | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:15287819 | lld:pubmed |
