Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
2007-10-24
pubmed:abstractText
In a small chromosomal region, a number of polymorphisms may be both linked to and associated with a disease. Distinguishing the potential causal sites from those indirectly associated due to linkage disequilibrium (LD) with a causal site is an important problem. This problem may be approached by determining which of the associations can explain the observed linkage signal. Recently, several methods have been proposed to aid in the identification of disease associated polymorphisms that may explain an observed linkage signal, using genotype data from affected sib pairs (ASPs) [Li et al. [2005] Am. J. Hum. Genet. 76:934-949; Sun et al. [2002] Am. J. Hum. Genet. 70:399-411]. These methods can be used to test the null hypothesis that a candidate single nucleotide polymorphism (SNP) is the sole causal variant in the region, or is in complete LD with the sole causal variant in the region. We extend variations of these methods to test for complete LD between a disease locus and haplotypes composed of two or more tightly linked candidate SNPs. We study properties of the proposed methods by simulation and apply them to type 1 diabetes data for ASPs and their parents at candidate SNP and microsatellite marker loci in the Insulin (INS) gene region.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-10775523, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-11017071, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-11055372, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-11731797, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-11791210, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-14872409, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-15220214, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-15657872, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-15877278, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-16252236, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-16374834, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-16451657, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-16451703, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-16642434, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-16907705, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-3074732, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-3666445, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-8651312, http://linkedlifedata.com/resource/pubmed/commentcorrection/17508343-9345087
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0741-0395
pubmed:author
pubmed:issnType
Print
pubmed:volume
31
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
727-40
pubmed:dateRevised
2011-11-17
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Exploring causality via identification of SNPs or haplotypes responsible for a linkage signal.
pubmed:affiliation
Department of Medical Genetics, University of Cambridge, UK. biernacka.joanna@mayo.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't