Emerging technologies make it possible for the first time to genotype hundreds of thousands of single nucleotide polymorphisms (SNPs) simultaneously, enabling whole genome association studies. Using empirical genotype data from the International HapMap Project, we evaluate the extent to which the sets of SNPs contained on two whole genome genotyping arrays capture common SNPs across the genome, and find that the majority of common SNPs are well captured by these products either directly or through linkage disequilibrium (LD). We explore analytical strategies that utilize HapMap data to improve power of association studies conducted with these fixed sets of markers, and show that inclusion of specified haplotype tests in the downstream analysis can increase the fraction of common variants captured by 25% to 100%. Finally, a Bayesian approach to association analysis can improve power by weighting the likelihood of each statistical test detecting a true positive signal to reflect the number of putative causal alleles to which it is correlated.
This page will blog evaluations and results regarding those products, uploaded in order to contribute to the current global effort by the human genetics community to dissect the connections between genotypes and medically meaningful phenotypes by the means of whole-genome association studies.
Release 1: Feb 20, 2006
Initial product evaluation and tests based on HapMap Phase II
- Affymetrix GeneChip100k
- Affymetrix GeneChip500k
- Illumina BeadArray HumanMap300k (preliminary list)
Release 2: March 18, 2006
Updated product evaluation and tests
- Illumina BeadArray HumanMap300k (publicly announced list)
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