Linked Life Data

10597524

Source:http://linkedlifedata.com/resource/pubmed/id/10597524

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2000-1-24
pubmed:abstractText
A Bayesian method for multipoint mapping of disease genes based on Markov chain Monte Carlo algorithms was applied to the simulated GAW11 data (Study 2). The method is based on repeated Gibbs and more general Metropolis-Hastings steps. For simplicity we assumed a single disease locus model with two alleles. A normal distribution for the underlying latent variable of the qualitative phenotype was assumed. Based on a single replicate of the data no clear evidence of any of the genes underlying the simulated disease was found. However, when three replicates were combined the method was able to locate the locus C correctly on chromosome 3.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0741-0395
pubmed:author
pubmed:issnType
Print
pubmed:volume
17 Suppl 1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S743-8
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
A Bayesian Markov chain Monte Carlo approach to map disease genes in simulated GAW11 data.
pubmed:affiliation
Rolf Nevanlinna Institute, University of Helsinki, Finland.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't