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Nat Methods. 2015 Apr;12(4):332-4. doi: 10.1038/nmeth.3285. Epub 2015 Feb 9.

Accurate liability estimation improves power in ascertained case-control studies.

Author information

1
Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel.
2
eScience Group, Microsoft Research, Los Angeles, California, USA.

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.

PMID:
25664543
DOI:
10.1038/nmeth.3285
[Indexed for MEDLINE]

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