Mar 8, 2016

A Unified Framework for Variance Component Estimation with Summary Statistics in Genome-wide Association Studies

BioRxiv : the Preprint Server for Biology
Xiang Zhou

Abstract

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs -- the restricted maximum likelihood estimation method (REML) -- suffers from several important drawbacks: REML is computationally slow, requires individual-level genotypes and phenotypes, and produces biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criteria, and brings two seemingly unrelated methods -- the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC) -- into the same unified framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics and is faster to compute. We also provide an exact estimation form of LDSC to yield unbiased and more accurate estimates with calibrated confidence intervals. A key feature of our method is that it can effectively use a small random subset of individuals for computation while still produ...Continue Reading

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Mentioned in this Paper

Computer Software
Genome-Wide Association Study
Genetic Association Studies
Hepatic Encephalopathy
Bud - plant part
Simulation
Senior Moment
Gemma (invertebrate)
Case-Control Studies
Computed (Procedure)

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