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Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change

Pejman Mohammadi, Stephane E Castel, Andrew A Brown, Tuuli Lappalainen
doi: https://doi.org/10.1101/078717
Pejman Mohammadi
1New York Genome Center, New York, NY, USA.
2Department of Systems Biology, Columbia University, New York, NY, USA.
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Stephane E Castel
1New York Genome Center, New York, NY, USA.
2Department of Systems Biology, Columbia University, New York, NY, USA.
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Andrew A Brown
3Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
4Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, 1211, Switzerland
5Swiss Institute of Bioinformatics, Geneva, 1211, Switzerland
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Tuuli Lappalainen
1New York Genome Center, New York, NY, USA.
2Department of Systems Biology, Columbia University, New York, NY, USA.
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Abstract

Mapping cis-acting expression quantitative trait loci (cis-eQTL) has become a popular approach for characterizing proximal genetic regulatory variants. However, measures used for quantifying the effect size of cis-eQTLs have been inconsistent and poorly defined. In this paper, we describe log allelic fold change (aFC) as a biologically interpretable and mathematically convenient unit that represents the magnitude of expression change associated with a given genetic variant. This measure is mathematically independent from expression level and allele frequency, applicable to multi-allelic variants, and generalizable to multiple independent variants. We provide tools and guidelines for estimating aFC from eQTL and allelic expression data sets, and apply it to 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 these eQTLs are independent in their regulatory activity. In summary, aFC is a solid measure of cis-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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 30, 2016.
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Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change
Pejman Mohammadi, Stephane E Castel, Andrew A Brown, Tuuli Lappalainen
bioRxiv 078717; doi: https://doi.org/10.1101/078717
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Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change
Pejman Mohammadi, Stephane E Castel, Andrew A Brown, Tuuli Lappalainen
bioRxiv 078717; doi: https://doi.org/10.1101/078717

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