Multistage Sequence/Array Design

• Activity Number: 253
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Thomas J Hoffmann*+ and John Witte
• Companies: University of California at San Francisco and University of California at San Francisco
• Keywords: genetics ; rare variants ; multi-stage design ; imputation

Abstract

Recent findings suggest that rare variants play an important role in disease, and studies have moved to studying rare variants to explain more of the missing genetic heritability. There are several different study designs for rare variants. One option would be to sequence everyone. On the other extreme, one could genotype everyone on arrays, and then impute everyone using existing sequence data (e.g., the 1000 Genomes Project). However, if disease causing rare variants are unique to a certain population, then one needs to directly sequence individuals from that population to detect these rare variants. Although sequencing costs are decreasing, it is also generally not cost-effective to sequence everyone, unless one is studying a rare, highly penetrant diseases, e.g., in a family, as there will be little power. An alternative design is to compromise with a multi-stage approach in which one sequences a subset of individuals, and use these data to impute into the rest of the subjects genotyped on an array.