Using In silico LD clumping and meta-analysis of genome-wide datasets as a complementary tool to investigate and validate new candidate biomarkers in Alzheimer's disease.

ABSTRACT: Despite the recent wealth of genome-wide association studies, insufficient power may explain why much of the heritable contribution to common diseases remains hidden. As different SNP panels are genotyped by commercial chips, increasing study power through meta-analysis is made problematic. To address these power issues we suggest an approach which permits meta-analysis of candidate SNPs from multiple GWAS. By identifying correlated SNPs from different platforms (r(2)=1), using PLINK's 'clumping' method, we generated combined p-values (using Fisher's combined and random effects meta-analysis) for each clump. P-values were corrected for the number of clumps (representing the number of independent tests). We also explored to what extent commercial platforms tag HapMap SNPs within these candi

SUBMITTER: Medway C 

PROVIDER: S-EPMC3076759 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature