Functional enrichment of alternative splicing events with NEASE reveals insights into tissue identity and diseases

被引:0
作者
Zakaria Louadi
Maria L. Elkjaer
Melissa Klug
Chit Tong Lio
Amit Fenn
Zsolt Illes
Dario Bongiovanni
Jan Baumbach
Tim Kacprowski
Markus List
Olga Tsoy
机构
[1] Technical University of Munich,Chair of Experimental Bioinformatics, TUM School of Life Sciences
[2] University of Hamburg,Institute for Computational Systems Biology
[3] Odense University Hospital,Department of Neurology
[4] University of Southern Denmark,Institute of Clinical Research
[5] University of Southern Denmark,Institute of Molecular Medicine
[6] University hospital rechts der Isar,Department of Internal Medicine I, School of Medicine
[7] Technical University of Munich,Department of Cardiovascular Medicine
[8] German Center for Cardiovascular Research (DZHK),Institute of Mathematics and Computer Science
[9] Partner Site Munich Heart Alliance,Division Data Science in Biomedicine
[10] Humanitas Clinical and Research Center IRCCS and Humanitas University,Braunschweig Integrated Centre of Systems Biology (BRICS)
[11] University of Southern Denmark,undefined
[12] Peter L. Reichertz Institute for Medical Informatics of Technische Universität Braunschweig and Hannover Medical School,undefined
[13] TU Braunschweig,undefined
来源
Genome Biology | / 22卷
关键词
Alternative splicing; Differential splicing; Functional enrichment; Systems biology; Protein-protein interactions; Disease pathways; Platelet activation; Multiple sclerosis; Dilated cardiomyopathy;
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摘要
Alternative splicing (AS) is an important aspect of gene regulation. Nevertheless, its role in molecular processes and pathobiology is far from understood. A roadblock is that tools for the functional analysis of AS-set events are lacking. To mitigate this, we developed NEASE, a tool integrating pathways with structural annotations of protein-protein interactions to functionally characterize AS events. We show in four application cases how NEASE can identify pathways contributing to tissue identity and cell type development, and how it highlights splicing-related biomarkers. With a unique view on AS, NEASE generates unique and meaningful biological insights complementary to classical pathways analysis.
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