In silico evaluation of DNA-pooled allelotyping versus individual genotyping for genome-wide association analysis of complex disease.

Abstract

Recent advances in single nucleotide polymorphism (SNP) genotyping techniques, public databases, and genomic knowledge via the Human Genome Project and the Haplotype Mapping project (HapMap) allow for true genome-wide association (GWA) analysis for common complex diseases such as heart disease, diabetes, and Alzheimer’s. A major obstacle in genome-wide association analysis is the prohibitively high cost of projects that require genotyping hundreds, even thousands, of individuals in order to achieve appropriate statistical significance. One potential solution to the prohibitive cost is to combine or pool the DNA of case and control individuals and to use pooled genotyping or ”allelotyping” for association analysis by determining the genotype allele frequency differences between case and control populations. While pooling can dramatically increase efficiencies by lowering cost and time, it also introduces additional sources of error and noise. In this study, we comparatively examine DNA pooled genotyping versus individual genotyping for genome-wide association analysis of complex disease. Our work has created a system and process that allows for the direct evaluation and comparison of pooled genotyping versus individual genotyping by using and modifying existing bioinformatics tools. Our results show that pooled GWA studies are limited to resolving complex disease with medium to high relative risks ratios. Pooling errors have a very large effect on the overall statistical significance of a pooled GWA. Genotyping errors have a modest effect on pooled and individual GWA which is much less in magnitude to pooling errors.