Contribution to Book
A Population Based Confidence Set Inference Method for SNPs that Regulate Quantitative Phenotypes
Ordered Data Analysis, Modeling and Health Research Methods
(2015)
Abstract
The increased use of genome-wide association studies based on genetic maps consisting of hundreds of thousands of SNPs has prompted the need for methods that can be used in preliminary analyses to limit the number of SNPs investigated in follow-up studies. I introduce a Confidence Set Inference method for independent individuals that can be used as a first step in association studies to derive a set of SNPs that contribute at least a specific percentage to the total variance of a quantitative trait. The main advantage of the method is that it allows control over the confidence level with which one can identify genes with specific effects on the genetic variance of the trait of interest. Developed in the framework of linear models, the method can efficiently incorporate information on pertinent covariates. I investigate the properties of the method through an extensive simulation study under various simple inheritance models and compare its performance to that of a standard association approach as it is implemented in the software package Merlin.
Keywords
- GWAS,
- Association studies,
- Confidence sets,
- Fine mapping,
- CSI
Disciplines
Publication Date
2015
Editor
Pankaj K. Choudhary, Chaitra H. Nagaraja, Hon Keung Tony Ng
Publisher
Springer
Series
Springer Proceedings in Mathematics & Statistics
DOI
10.1007/978-3-319-25433-3_14
Citation Information
Charalampos Papachristou. "A Population Based Confidence Set Inference Method for SNPs that Regulate Quantitative Phenotypes" Ordered Data Analysis, Modeling and Health Research Methods Vol. 149 (2015) Available at: http://works.bepress.com/charalampos-papachristou/2/