TwinEQTL: ultrafast and powerful association analysis for eQTL and GWAS in twin studies

Abstract We develop a computationally efficient alternative, TwinEQTL, to a linear mixed-effects model for twin genome-wide association study data. Instead of analyzing all twin samples together with linear mixed-effects model, TwinEQTL first splits twin samples into 2 independent groups on which mu...

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Bibliographic Details
Published in:	Genetics (Austin) 2022-07, Vol.221 (4)
Main Authors:	Xia, Kai, Shabalin, Andrey A, Yin, Zhaoyu, Chung, Wonil, Sullivan, Patrick F, Wright, Fred A, Styner, Martin, Gilmore, John H, Santelli, Rebecca C, Zou, Fei
Format:	Article
Language:	eng
Subjects:	Algorithms Association analysis Computational efficiency Computer applications Gene expression Gene Frequency Genetics Genome-wide association studies Genome-Wide Association Study - methods Genomes Humans Investigation Linear Models Mathematical models Medicin och hälsovetenskap Nucleotides Polymorphism Polymorphism, Single Nucleotide Quantitative Trait Loci Regression analysis Single-nucleotide polymorphism Statistical analysis Statistical tests Twin studies Twins
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Summary:	Abstract We develop a computationally efficient alternative, TwinEQTL, to a linear mixed-effects model for twin genome-wide association study data. Instead of analyzing all twin samples together with linear mixed-effects model, TwinEQTL first splits twin samples into 2 independent groups on which multiple linear regression analysis can be validly performed separately, followed by an appropriate meta-analysis-like approach to combine the 2 nonindependent test results. Through mathematical derivations, we prove the validity of TwinEQTL algorithm and show that the correlation between 2 dependent test statistics at each single-nucleotide polymorphism is independent of its minor allele frequency. Thus, the correlation is constant across all single-nucleotide polymorphisms. Through simulations, we show empirically that TwinEQTL has well controlled type I error with negligible power loss compared with the gold-standard linear mixed-effects models. To accommodate expression quantitative loci analysis with twin subjects, we further implement TwinEQTL into an R package with much improved computational efficiency. Our approaches provide a significant leap in terms of computing speed for genome-wide association study and expression quantitative loci analysis with twin samples.
ISSN:	1943-2631 0016-6731 1943-2631