Journal
GENETICS
Volume 180, Issue 4, Pages 1909-1925Publisher
GENETICS SOCIETY AMERICA
DOI: 10.1534/genetics.108.094201
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Funding
- NCRR NIH HHS [C06 RR017588, P41 RR08605, P41 RR008605] Funding Source: Medline
- NHLBI NIH HHS [K25 HL080079, 1K25HL080079, K25 HL080079-03, K25 HL080079-04] Funding Source: Medline
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In genomewide 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 about how these technical confounding factors affect eQTL analyses and how to correct for these factors. Our analysis of data sets with biological replicates suggests that it. is this intersample 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 intersample correlation of expression measurements in eQTL mapping. Applying our intersample correlation emended (ICE) eQTL mapping method to mouse, yeast, and human identifies many more cis association 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.
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