Linked Life Data

18466504

Source:http://linkedlifedata.com/resource/pubmed/id/18466504

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-5-9
pubmed:abstractText
Recent studies have shown that linkage disequilibrium (LD) between single-nucleotide polymorphism (SNP) markers is widespread. Assuming linkage equilibrium has been shown to cause false positives in linkage studies where parental genotypes are not available. Therefore, linkage analysis methods that can deal with LD are required to accurately analyze SNP marker data sets. We compared three approaches to deal with LD between markers: 1) The clustered-markers approach implemented in the computer program MERLIN; 2) The standard hidden Markov model (HMM) multipoint model augmented with a first-order Markov model for the allele frequencies of the founders, in which we considered both a Bayesian and a maximum-likelihood implementation of this approach; 3) The 'independent' SNPs approach, i.e., removing SNPs from the data set until the remaining SNPs have low levels of LD.We evaluated these approaches on the Illumina 6K SNP data set of affected sib-pairs of Problem 2. We found that the first-order Markov model was able to account for most of the strong LD in this data set. The difference between the Bayesian and maximum- likelihood implementation was small. An advantage of the first-order Markov model is that it does not require the user to specify parameters.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:issn
1753-6561
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
1 Suppl 1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S159
pubmed:dateRevised
2010-9-22
pubmed:year
2007
pubmed:articleTitle
Modeling linkage disequilibrium in exact linkage computations: a comparison of first-order Markov approaches and the clustered-markers approach.
pubmed:affiliation
Department of Biophysics, Radboud University, 126 Geert Grooteplein 21, Nijmegen, Gelderland 6525EZ The Netherlands. k.albers@science.ru.nl
pubmed:publicationType
Journal Article