Journal Article

Testing for an Unusual Distribution of Rare Variants

Voight, Benjamin F., Devlin, Bernie, Kathiresan, Sekar, Purcell, Shaun M., Neale, Benjamin M., Rivas, Manuel A., Orho-Melander, Marju, Daly, Mark J., Roeder, Kathryn, Altshuler, David

2011

Overview

Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Algorithms / Analysis of Variance / Autism / Cholesterol / Clinical Medicine / Computational Biology/Genomics / Computer Simulation / Data Interpretation, Statistical / Disease / DNA sequencing / Endocrinology and Diabetes / Endokrinologi och diabetes / Genetic Variation / Genetics and Genomics/Complex Traits / Genetics and Genomics/Genetics of Disease / Genetics and Genomics/Medical Genetics / Genomes / Genotype & phenotype / Heart attacks / High-Throughput Nucleotide Sequencing - statistics & numerical data / Humans / Hypotheses / Klinisk medicin / Mathematics/Statistics / Medical and Health Sciences / Medical research / Medicin och hälsovetenskap / Methods / Models, Statistical / Mutation / Nucleotide sequencing / Single nucleotide polymorphisms / Studies