Skip Navigation


Biostatistics Advance Access originally published online on January 27, 2006
Biostatistics 2006 7(3):339-354; doi:10.1093/biostatistics/kxj020
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
7/3/339    most recent
kxj020v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Prentice, R. L.
Right arrow Articles by QI, L.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Prentice, R. L.
Right arrow Articles by QI, L.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Aspects of the design and analysis of high-dimensional SNP studies for disease risk estimation

Ross L. Prentice* and Lihong QI

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA rprentic{at}fhcrc.org

* To whom correspondence should be addressed.

The state of readiness for high-dimensional single nucleotide polymorphism (SNP) epidemiologic association studies is described, as background for a discussion of statistical aspects of case–control study design and analysis. Specifically, the important role that multistage designs can play in the elimination of false-positive associations and in the control of study costs will be noted. Also, the trade-offs associated with using pooled DNA at early design stages for additional important cost reductions will be discussed in some detail. An odds ratio approach to relating SNP alleles to disease risk using pooled DNA will be proposed, in conjunction with a simple empirical variance estimator, based on comparisons among log-odds ratio estimators from distinct pairs of case and control pools. Simulation studies will be presented to evaluate the moderate sample size properties of such multistage designs and estimation procedures. The design of an ongoing three-stage study in the Women's Health Initiative to relate 250 000 SNPs to the risk of coronary heart disease, stroke, and breast cancer will provide illustration, and will be used to motivate the choice of simulation configurations.

Keywords: Case–control; Cohort; Genetic association; High-dimensional data; Multistage design; Odds ratio; Pooled DNA; Single nucleotide polymorphism


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BiostatisticsHome page
H. Zhong and R. L. Prentice
Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies
Biostat., February 28, 2008; (2008) kxn001v1.
[Abstract] [Full Text] [PDF]

Home page
 BiostatisticsHome page
T. Johnson
Bayesian method for gene detection and mapping, using a case and control design and DNA pooling
Biostat., July 1, 2007; 8(3): 546 - 565.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.