Linked Life Data

20828390

Source:http://linkedlifedata.com/resource/pubmed/id/20828390

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2010-10-5
pubmed:abstractText
Genome-wide association studies (GWAS) are a widely used study design for detecting genetic causes of complex diseases. Current studies provide good coverage of common causal SNPs, but not rare ones. A popular method to detect rare causal variants is haplotype testing. A disadvantage of this approach is that many parameters are estimated simultaneously, which can mean a loss of power and slower fitting to large datasets.Haplotype testing effectively tests both the allele frequencies and the linkage disequilibrium (LD) structure of the data. LD has previously been shown to be mostly attributable to LD between adjacent SNPs. We propose a generalised linear model (GLM) which models the effects of each SNP in a region as well as the statistical interactions between adjacent pairs. This is compared to two other commonly used multimarker GLMs: one with a main-effect parameter for each SNP; one with a parameter for each haplotype.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1471-2156
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
80
pubmed:dateRevised
2010-11-4
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Comparison of multimarker logistic regression models, with application to a genomewide scan of schizophrenia.
pubmed:affiliation
MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 0SR, UK. james.wason@mrc-bsu.cam.ac.uk.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural