@article {30,
	title = {Quantifying the regulatory effect size of -acting genetic variation using allelic fold change.},
	journal = {Genome Res},
	volume = {27},
	year = {2017},
	month = {2017 11},
	pages = {1872-1884},
	abstract = {<p>Mapping -acting expression quantitative trait loci (-eQTL) has become a popular approach for characterizing proximal genetic regulatory variants. In this paper, we describe and characterize log allelic fold change (aFC), the magnitude of expression change associated with a given genetic variant, as a biologically interpretable unit for quantifying the effect size of -eQTLs and a mathematically convenient approach for systematic modeling of -regulation. This measure is mathematically independent from expression level and allele frequency, additive, applicable to multiallelic variants, and generalizable to multiple independent variants. We provide efficient tools and guidelines for estimating aFC from both eQTL and allelic expression data sets and apply it to Genotype Tissue Expression (GTEx) data. We show that aFC estimates independently derived from eQTL and allelic expression data are highly consistent, and identify technical and biological correlates of eQTL effect size. We generalize aFC to analyze genes with two eQTLs in GTEx and show that in nearly all cases the two eQTLs act independently in regulating gene expression. In summary, aFC is a solid measure of -regulatory effect size that allows quantitative interpretation of cellular regulatory events from population data, and it is a valuable approach for investigating novel aspects of eQTL data sets.</p>},
	keywords = {Alleles, Databases, Genetic, Gene Expression, Gene Expression Profiling, Gene Regulatory Networks, Genetic Variation, Humans, Models, Theoretical, Quantitative Trait Loci},
	issn = {1549-5469},
	doi = {10.1101/gr.216747.116},
	author = {Mohammadi, Pejman and Castel, Stephane E and Brown, Andrew A and Lappalainen, Tuuli}
}
