Genetic analysis of biological pathway data through genomic randomization.

ABSTRACT: Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of smaller effect size are not detected within a single allele analysis framework. Thus, small main effects and potential epistatic effects are not consistently observed in GWAS using standard analytical approaches that consider only single SNP alleles. Here, we propose unique methodology that aggregates variants of interest (for example, genes in a biological pathway) using GWAS results. Multiple testing and type I error concerns are minimized using empirical genomic randomization to estimate significance. Ran

SUBMITTER: Yaspan BL 

PROVIDER: S-EPMC3107984 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature