Large-scale characterization of public database SNPs causing non-synonymous changes in three ethnic groups.

Single nucleotide polymorphisms (SNPs) that lead to non-synonymous changes in proteins may have functional effects and be subject to selection. Hence they are of particular interest in the study of genetic diseases. We have genotyped approximately 28,000 such SNPs in three ethnic populations (the HapMap plates) and ten primate species and analyzed these data for evidence of selection.

Allele quantification using molecular inversion probes (MIP).

Detection of genomic copy number changes has been an important research area, especially in cancer. Several high-throughput technologies have been developed to detect these changes. Features that are important for the utility of technologies assessing copy number changes include the ability to interrogate regions of interest at the desired density as well as the ability to differentiate the two homologs.

Optimal genotype determination in highly multiplexed SNP data.

High-throughput genotyping technologies that enable large association studies are already available. Tools for genotype determination starting from raw signal intensities need to be automated, robust, and flexible to provide optimal genotype determination given the specific requirements of a study. The key metrics describing the performance of a custom genotyping study are assay conversion, call rate, and genotype accuracy.

Population structure, differential bias and genomic control in a large-scale, case-control association study.

The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.