Comparison of multimarker logistic regression models, with application to a genomewide scan of schizophrenia.

ABSTRACT:

Background

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

SUBMITTER: Wason JM 

PROVIDER: S-EPMC2949738 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature