Accurate liability estimation improves power in ascertained case-control studies

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


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; 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biostatistics
  • Case-Control Studies*
  • Genome-Wide Association Study / methods*
  • Humans
  • Models, Theoretical
  • Multiple Sclerosis / genetics
  • Sample Size