Controlling for false positive findings of
trans-hubs in expression quantitative trait loci mappingJie Peng
1, Pei Wang 2 and Hua Tang 31Department 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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