Abstract
To find the correlations between genome-wide gene expression variations and sequence polymorphisms in inbred cross populations, we developed a statistical method to claim expression quantitative trait loci (eQTL) in a genome. The method is based on multiple interval mapping (MIM), a model selection procedure, and uses false discovery rate (FDR) to measure the statistical significance of the large number of eQTL. We compared our method with a similar procedure proposed by Storey et al. and found that our method can be more powerful. We identified the features in the two methods that resulted in different statistical powers for eQTL detection, and confirmed them by simulation. We organized our computational procedure in an R package which can estimate FDR for positive findings from similar model selection procedures. The R package, MIM-eQTL, can be found at http://www.statgen.ncsu.edu/~wzou/MIM.eQTL.html.
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Acknowledgement
The authors sincerely thank Dr. Leonid Kruglyak for the access of the wonderful yeast data set.
Funding
This work was partially supported by the USDA Cooperative State Research, Education and Extension Service, Grant Number 2005-00754.
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Zou, W., Zeng, ZB. Multiple interval mapping for gene expression QTL analysis. Genetica 137, 125–134 (2009). https://doi.org/10.1007/s10709-009-9365-z
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DOI: https://doi.org/10.1007/s10709-009-9365-z