Linked Life Data

17164795

Source:http://linkedlifedata.com/resource/pubmed/id/17164795

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2007-1-18
pubmed:abstractText
There is great interest in the use of tagging single nucleotide polymorphisms (tSNPs) to facilitate association studies of complex diseases. This is based on the premise that a minimum set of tSNPs may be sufficient to capture most of the variation in certain regions of the human genome. Several methods have been described to select tSNPs, based on either haplotype-block structure or independent of the underlying block structure. In this paper, we compare eight methods for choosing tSNPs in 10 representative resequenced candidate genes (a total of 194.2 kb) with different levels of linkage disequilibrium (LD) in a sample of European-Americans. We compared tagging efficiency (TE) and prediction accuracy of tSNPs identified by these methods, as a function of several factors, including LD level, minor allele frequency, and tagging criteria. We also assessed tagging consistency between each method. We found that tSNPs selected based on the methods Haplotype Diversity and Haplotype r2 provided the highest TE, whereas the prediction accuracy was comparable among different methods. Tagging consistency between different methods of tSNPs selection was poor. This work demonstrates that when tSNPs-based association studies are undertaken, the choice of method for selecting tSNPs requires careful consideration.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1018-4813
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
228-36
pubmed:dateRevised
2007-12-3
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Methods for the selection of tagging SNPs: a comparison of tagging efficiency and performance.
pubmed:affiliation
Division of Cardiovascular Diseases, Mayo Clinic and Foundation, Rochester, MN 55905, USA.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, N.I.H., Extramural