Abstract
Mapping expression quantitative trait loci (eQTLs) is an important avenue to identify putative genetic variants in regulatory regions. Famed eQTL mapping methods exploit the mean effects of locus-wise genetic variants on expression quantitative traits. Despite their successes, such methods are suboptimal because they neglect high-order heterogeneity inherent in genetic variants and covariates. High-order effects of observed loci are common due to their connections to various latent factors, i.e., latent interactions among genes and environmental factors. In this chapter, we introduce a new scheme to harmoniously integrate mean and high-order effects of genetic variants on expression quantitative trait. We rigorously evaluate its validity and utility of signal augmentation.
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Acknowledgments
This work was partially funded by the National Institutes of Health grants R01DK091369, R01MH097018, and RF1AG052476. The funders had no role in study design, data analysis, preparation of the manuscript, or decision to publish.
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Qin, H., Ouyang, W., Zhao, J. (2020). High-Order Association Mapping for Expression Quantitative Trait Loci. In: Shi, X. (eds) eQTL Analysis. Methods in Molecular Biology, vol 2082. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0026-9_10
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DOI: https://doi.org/10.1007/978-1-0716-0026-9_10
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Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-0025-2
Online ISBN: 978-1-0716-0026-9
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