Evaluating haplotype effects in case-control studies via penalized-likelihood approaches: prospective or retrospective analysis?
Article first published online: 22 NOV 2010
© 2010 Wiley-Liss, Inc.
Volume 34, Issue 8, pages 892–911, December 2010
How to Cite
Koehler, M. L., Bondell, H. D. and Tzeng, J.-Y. (2010), Evaluating haplotype effects in case-control studies via penalized-likelihood approaches: prospective or retrospective analysis?. Genet. Epidemiol., 34: 892–911. doi: 10.1002/gepi.20545
- Issue published online: 22 NOV 2010
- Article first published online: 22 NOV 2010
- Manuscript Accepted: 15 SEP 2010
- Manuscript Revised: 3 SEP 2010
- Manuscript Received: 29 APR 2010
- NIH. Grant Numbers: 5RO1-HL049609-14, 1R01-AG021917-01A1; T32GM081057, R01 MH084022-01, R01 MH084022-01, 1P01-CA142538-0, R01 MH084022-01, 1P01-CA142538-01
- University of Minnesota; Minnesota Supercomputing Institute
- GAW. Grant Numbers: R01-GM031575, AR44422
- NSF. Grant Number: DMS-0705968
- haplotype-based association analysis;
- variable selection;
- regularized regression;
- prospective likelihood;
- retrospective likelihood
Penalized likelihood methods have become increasingly popular in recent years for evaluating haplotype-phenotype association in case-control studies. Although a retrospective likelihood is dictated by the sampling scheme, these penalized methods are typically built on prospective likelihoods due to their modeling simplicity and computational feasibility. It has been well documented that for unpenalized methods, prospective analyses of case-control data can be valid but less efficient than their retrospective counterparts when testing for association, and result in substantial bias when estimating the haplotype effects. For penalized methods, which combine effect estimation and testing in one step, the impact of using a prospective likelihood is not clear. In this work, we examine the consequences of ignoring the sampling scheme for haplotype-based penalized likelihood methods. Our results suggest that the impact of prospective analyses depends on (1) the underlying genetic mode and (2) the genetic model adopted in the analysis. When the correct genetic model is used, the difference between the two analyses is negligible for additive and slight for dominant haplotype effects. For recessive haplotype effects, the more appropriate retrospective likelihood clearly outperforms the prospective likelihood. If an additive model is incorrectly used, as the true underlying genetic mode is unknown a priori, both retrospective and prospective penalized methods suffer from a sizeable power loss and increase in bias. The impact of using the incorrect genetic model is much bigger on retrospective analyses than prospective analyses, and results in comparable performances for both methods. An application of these methods to the Genetic Analysis Workshop 15 rheumatoid arthritis data is provided. Genet. Epidemiol. 34:892–911, 2010. © 2010 Wiley-Liss, Inc.