Fast and Accurate Construction of Confidence Intervals for Heritability.

ABSTRACT: Estimation of heritability is fundamental in genetic studies. Recently, heritability estimation using linear mixed models (LMMs) has gained popularity because these estimates can be obtained from unrelated individuals collected in genome-wide association studies. Typically, heritability estimation under LMMs uses the restricted maximum likelihood (REML) approach. Existing methods for the construction of confidence intervals and estimators of SEs for REML rely on asymptotic properties. However, these assumptions are often violated because of the bounded parameter space, statistical dependencies, and limited sample size, leading to biased estimates and inflated or deflated confidence intervals. Here, we show that the estimation of confidence intervals by state-of-the-art methods is inaccurat

SUBMITTER: Schweiger R 

PROVIDER: S-EPMC4908190 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature