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CAGI 5 splicing challenge: Improved exon skipping and intron retention predictions with MMSplice
Author(s) -
Cheng Jun,
Çelik Muhammed Hasan,
Nguyen Thi Yen Duong,
Avsec Žiga,
Gagneur Julien
Publication year - 2019
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23788
Subject(s) - rna splicing , biology , intron , exon skipping , computational biology , exon , plug in , genome , genetics , alternative splicing , gene , computer science , rna , programming language
Pathogenic genetic variants often primarily affect splicing. However, it remains difficult to quantitatively predict whether and how genetic variants affect splicing. In 2018, the fifth edition of the Critical Assessment of Genome Interpretation proposed two splicing prediction challenges based on experimental perturbation assays: Vex‐seq, assessing exon skipping, and MaPSy, assessing splicing efficiency. We developed a modular modeling framework, MMSplice, the performance of which was among the best on both challenges. Here we provide insights into the modeling assumptions of MMSplice and its individual modules. We furthermore illustrate how MMSplice can be applied in practice for individual genome interpretation, using the MMSplice VEP plugin and the Kipoi variant interpretation plugin, which are directly applicable to VCF files.