sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression
Yuan He, Surya B. Chhetri, Marios Arvanitis, Kaushik Srinivasan, François Aguet, Kristin Ardlie, Alvaro Barbeira, Rodrigo Bonazzola, Hae Kyung Im, Christopher D. Brown, Alexis Battle
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.