Using ascertainment for targeted resequencing to increase power to identify causal variants
Year: 2011
Type: article
Abstract: Researchers continue to use genome-wide association studies (GWAS) to find the genetic markers associated with disease. Recent studies have added to the typical two-stage analysis a third stage that uses targeted resequencing on a randomly selected subset of the cases to detect the causal single-nucleotide polymorphism (SNP). We propose a design for targeted resequencing that increases the power to detect the causal variant. The design features an ascertainment scheme wherein only those cases with the presence of a risk allele are selected for targeted resequencing. We simulated a disease with a single causal SNP to evaluate our method versus a targeted resequencing design using randomly selected individuals. The simulation studies showed that ascertaining individuals for the targeted resequencing can substantially increase the power to detect a causal SNP, without increasing the false-positive rate.
Source: Statistics and Its Interface
Authors: B. Peng, C. Reyes-Gibby, S. Shete, M. D. Swartz
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: Bayesian Hierarchical Risk Models: Nutrition, Genes, & Environment Interactions, Statistical Methods for Gene Environment Interactions In Lung Cancer, G3703747017, A Mutational Model for Childhood Cancer, Mechanisms and Prevention of Environmental Disease, Genome Wide Association Study of Head and Neck Cancer, A Novel Bayesian Model Averaging Approach for Genome Wide Association Studies
OpenAlex ID: W2038069828