sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression

Yuan He; Surya B Chhetri; Marios Arvanitis; Kaushik Srinivasan; François Aguet; Kristin G Ardlie; Alvaro N Barbeira; Rodrigo Bonazzola; Hae Kyung Im; GTEx Consortium; Christopher D Brown; Alexis Battle

doi:10.1186/s13059-020-02129-6

sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression

Genome Biol. 2020 Sep 11;21(1):235. doi: 10.1186/s13059-020-02129-6.

Authors

Yuan He¹, Surya B Chhetri^{2

3}, Marios Arvanitis^{1

4}, Kaushik Srinivasan⁵, François Aguet⁶, Kristin G Ardlie⁶, Alvaro N Barbeira⁷, Rodrigo Bonazzola⁷, Hae Kyung Im⁷; GTEx Consortium; Christopher D Brown⁸, Alexis Battle^{9

10}

Affiliations

¹ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.
² HudsonAlpha Institute for Biotechnology, Huntsville, 35806, AL, USA.
³ Current Address: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.
⁴ Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, 21287, MD, USA.
⁵ Department of Computer Science, Johns Hopkins University, Baltimore, 21218, MD, USA.
⁶ The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁷ Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
⁸ Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, PA, USA. [email protected].
⁹ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA. [email protected].
¹⁰ Department of Computer Science, Johns Hopkins University, Baltimore, 21218, MD, USA. [email protected].

Abstract

Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), exhibits complex patterns of tissue-specific effects. Characterization of these patterns may allow us to better understand mechanisms of gene regulation and disease etiology. We develop a constrained matrix factorization model, sn-spMF, to learn patterns of tissue-sharing and apply it to 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors reflect tissues with known biological similarity and identify transcription factors that may mediate tissue-specific effects. sn-spMF, available at https://github.com/heyuan7676/ts_eQTLs , can be applied to learn biologically interpretable patterns of eQTL tissue-specificity and generate testable mechanistic hypotheses.

Keywords: Matrix factorization; Tissue-specific eQTLs; Transcription factors; Ubiquitous eQTLs.

Publication types

Evaluation Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Gene Expression Regulation*
Humans
Models, Genetic*
Quantitative Trait Loci*
Transcription Factors / metabolism*

Substances

Transcription Factors

Abstract

Publication types

MeSH terms

Substances

Grants and funding