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doi:10.1534/genetics.108.094201
A more recent version of this article appeared on December 1, 2008.
REGULAR RESEARCH PAPERS |
Accurate Discovery of Expression Quantitative Trait Loci Under Confounding from Spurious and Genuine Regulatory Hotspots
Hyun Min Kang 1, Chun Ye 1 and Eleazar Eskin 2*
1 UC San Diego
2 UCLA
* To whom correspondence should be addressed. E-mail: eeskin{at}cs.ucla.edu.
Submitted on July 21, 2008
Revised on August 26, 2008
Accepted on 9 September 2008
In genome wide mapping of expression quantitative trait loci (eQTL), it is widely believed that thousands of genes are trans-regulated by a small number of genomic regions called "regulatory hotspots", resulting in "trans-regulatory bands"; in an eQTL map. As several recent studies have demonstrated, technical confounding factors such as batch effects can complicate eQTL analysis by causing many spurious associations including spurious regulatory hotspots. Yet little is understood how these technical confounding factors affect eQTL analyses and how to correct for these factors. Our analysis of datasets with biological replicates suggests that it is this inter-sample correlation structure inherent in expression data that leads to spurious associations between genetic loci and a large number of transcripts inducing spurious regulatory hotspots. We propose a statistical method that corrects for the spurious associations caused by complex inter-sample correlation of expression measurements in eQTL mapping. Applying our Inter-sample Correlation Emended (ICE) eQTL mapping method to mouse, yeast, and human identifies many more cis associations while eliminating most of the spurious trans associations. The concordances of cis and trans associations have consistently increased between different replicates, tissues, and populations; demonstrating the higher accuracy of our method to identify real genetic effects.
Key Words: eQTL, genetical genomics, linear mixed model, regulatory hotspot, systematic confounding
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