Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping

Jie Peng 1, Pei Wang 2 and Hua Tang 3

1Department of Statistics, University of California, Davis, California 95616, USA

2Public Health Science, Fred Hutchinson Cancer

Research Center, 1100 Fairview Avenue North, Seattle 98109 Washington, USA and

3Department of Genetics, Stanford University, Stanford,

California 94305, USA

Corresponding author: jie@wald.ucdavis.edu

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Abstract:

In the fast-developing field of expression quantitative traits loci (eQTL) studies, much interest has been concentrated on detecting genomic regions containing transcriptional regulators that influence multiple expression phenotypes (trans-hubs). In this paper, we develop statistical methods for eQTL mapping and propose a new procedure for investigating candidate trans-hubs. We use data from the Genetic Analysis Workshop 15 to illustrate our methods. After correlations among expressions were accounted for, the previously detected trans-hubs are no longer significant. Our results suggest that conclusions regarding regulation hot spots should be treated with great caution.

Keywords: linkage analysis, score statistics, eQTL
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