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Cheng, J.* ; Çelik, M.H.* ; Kundaje, A.* ; Gagneur, J.

MTSplice predicts effects of genetic variants on tissue-specific splicing.

Genome Biol. 22:94 (2021)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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.
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Publication type Article: Journal article
Document type Scientific Article
Language english
Publication Year 2021
HGF-reported in Year 2021
ISSN (print) / ISBN 1474-760X
e-ISSN 1465-6906
Journal Genome Biology
Quellenangaben Volume: 22, Issue: 1, Pages: , Article Number: 94 Supplement: ,
Publisher BioMed Central
Publishing Place Campus, 4 Crinan St, London N1 9xw, England
Reviewing status Peer reviewed
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-503800-001
Grants NIH HHS
Scientific High Performance Computing in Bavaria KONWIHR
Scopus ID 85103744294
PubMed ID 33789710
Erfassungsdatum 2021-04-22