PCA-based bootstrap confidence interval tests for gene-disease association involving multiple SNPs.

ABSTRACT:

Background

Genetic association study is currently the primary vehicle for identification and characterization of disease-predisposing variant(s) which usually involves multiple single-nucleotide polymorphisms (SNPs) available. However, SNP-wise association tests raise concerns over multiple testing. Haplotype-based methods have the advantage of being able to account for correlations between neighbouring SNPs, yet assuming Hardy-Weinberg equilibrium (HWE) and potentially large number degrees of freedom can harm its statistical power and robustness. Approaches based on principal component analysis (PCA) are preferable in this regard but their performance varies with methods of extracting principal components (PCs).

Results

PCA-based bootstrap confidence interval test (PCA-BCIT

SUBMITTER: Peng Q 

PROVIDER: S-EPMC2825231 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature