Testing for an Unusual Distribution of Rare Variants

Abstract

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.

Cited by papers we hold 7

• Constitutively active SARM1 variants that induce neuropathy are enriched in ALS patients · 2022
  Not checked
• Privacy-Preserving Genome-Wide Association Study for Rare Mutations - A Secure FrameWork for Externalized Statistical Analysis · 2020
  Not checked
• The impact of rare and low-frequency genetic variants in common disease · 2017
  No notice
• Assessing the Power of Exome Chips. · 2015
  Not checked
• Rare coding mutations identified by sequencing of A lzheimer disease genome‐wide association studies loci · 2015
  No notice
• Review of Current Methods, Applications, and Data Management for the Bioinformatics Analysis of Whole Exome Sequencing · 2014
  Not checked
• Weighted pedigree-based statistics for testing the association of rare variants · 2012
  Not checked

Reads

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.