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Accurate liability estimation improves power in ascertained case-control studies

Item Type:Article
Title:Accurate liability estimation improves power in ascertained case-control studies
Creators Name:Weissbrod, O. and Lippert, C. and Geiger, D. and Heckerman, D.
Abstract:Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in nonrandomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (liability estimator as a phenotype; https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and we demonstrate that this can lead to a substantial power increase.
Keywords:Biostatistics, Case-Control Studies, Genome-Wide Association Study, Multiple Sclerosis, Sample Size, Theoretical Models
Source:Nature Methods
ISSN:1548-7091
Publisher:Nature Publishing Group (U.S.A.)
Volume:12
Number:4
Page Range:332-334
Date:April 2015
Official Publication:https://doi.org/10.1038/nmeth.3285
PubMed:View item in PubMed

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