MTSplice predicts effects of genetic variants on tissue-specific splicing

Cheng J, Celik MH, Kundaje A, Gagneur J (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Genome Biology

Book Volume: 22

Article Number: 94

Journal Issue: 1

DOI: 10.1186/s13059-021-02273-7

Abstract

We develop the free and open-source model Multi-tissue Splicing (MTSplice) to predict the effects of genetic variants on splicing of cassette exons in 56 human tissues. MTSplice combines MMSplice, which models constitutive regulatory sequences, with a new neural network that models tissue-specific regulatory sequences. MTSplice outperforms MMSplice on predicting tissue-specific variations associated with genetic variants in most tissues of the GTEx dataset, with largest improvements on brain tissues. Furthermore, MTSplice predicts that autism-associated de novo mutations are enriched for variants affecting splicing specifically in the brain. We foresee that MTSplice will aid interpreting variants associated with tissue-specific disorders.

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) Stanford University US United States (USA) (US)

How to cite

APA:

Cheng, J., Celik, M.H., Kundaje, A., & Gagneur, J. (2021). MTSplice predicts effects of genetic variants on tissue-specific splicing. Genome Biology, 22(1). https://doi.org/10.1186/s13059-021-02273-7

MLA:

Cheng, Jun, et al. "MTSplice predicts effects of genetic variants on tissue-specific splicing." Genome Biology 22.1 (2021).

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