Traditional genetic mapping has largely focused
on the identification of loci affecting one, or at most a few,
complex traits. Microarrays allow for measurement
of thousands of gene expression abundances,
themselves complex traits, and a number of
recent investigations have considered these
measurements as phenotypes in mapping studies.
These expression quantitative trait loci (eQTL)
mapping studies have demonstrated utility for
identifying candidate genes,
inferring not only correlative
but also causal relationships between modulator and modulated genes,
identifying regulatory networks, and
elucidating subclasses of clinical phenotypes.
As a result of these early successes, a number of eQTL mapping
efforts are now underway to localize the
genetic basis of gene expression.
Kendziorski and colleagues (2006) proposed a mixture over markers (MOM)
model to facilitate localization of eQTL.
The approach calculates transcript specific posterior probabilities
that quantify evidence in favor of mapping, while accounting for multiplicities
across both markers and transcripts. Details of the approach can be found in
Kendziorski et al., 2006.
We are currently updating the MOM code. A new version will be released in August, 2011. If you'd like the original version, please email me directly.
Kendziorski, C., M. Chen, M. Yuan, H. Lan, and A.D. Attie. Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping. Biometrics 62: 19-27, 2006 .
**The F2 data set used in the manuscript is available at GEO, accession number GSE3330.
Last Modified August 2010