Proximity Model for Expression Quantitative Trait Loci (eQTL) Detection
Version of Record online: 9 APR 2007
Volume 63, Issue 4, pages 1108–1116, December 2007
How to Cite
Gelfond, J. A. L., Ibrahim, J. G. and Zou, F. (2007), Proximity Model for Expression Quantitative Trait Loci (eQTL) Detection. Biometrics, 63: 1108–1116. doi: 10.1111/j.1541-0420.2007.00778.x
- Issue online: 9 APR 2007
- Version of Record online: 9 APR 2007
- Received October 2005.Revised November 2006. Accepted December 2006.
- Empirical Bayes;
- Gene expression;
- Mixture model;
- Quantitative trait loci
Summary Expression quantitative trait loci (eQTL) are loci or markers on the genomes that are associated with gene expression. It is well known to biologists that some (cis) genetic influences on expression occur over short distances on the genome while some (trans) influences can operate remotely. We use a log-linear model to place structure on the prior probability for genetic control of a transcript by a marker locus so that the loci that are closest to a transcript are given a higher prior probability of controlling that transcript to reflect the important role that genomic proximity can play in the regulation of expression. This proximity model is an extension of the mixture over marker (MOM) model for the simultaneous detection of cis and trans eQTL of Kendziorski (Kendziorski et al., 2006, Biometrics62(1), 19–27). The genomic locations of the transcripts are used to improve the accuracy of the posterior distribution for the location of the eQTL. We compare the MOM method to our extension with both simulated data and data sets of recombinant inbred mouse lines. We also discuss an extension of the MOM method to model multiple eQTLs, and find that many transcripts are likely associated with more than one eQTL.