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Assessing predictions of the impact of variants on splicing in CAGI5
Author(s) -
Mount Stephen M.,
Avsec Žiga,
Carmel Liran,
Casadio Rita,
Çelik Muhammed Hasan,
Chen Ken,
Cheng Jun,
Cohen Noa E.,
Fairbrother William G.,
Fenesh Tzila,
Gagneur Julien,
Gotea Valer,
Holzer Tamar,
Lin ChiaoFeng,
Martelli Pier Luigi,
Naito Tatsuhiko,
Nguyen Thi Yen Duong,
Savojardo Castrense,
Unger Ron,
Wang Robert,
Yang Yuedong,
Zhao Huiying
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.23869
Subject(s) - biology , rna splicing , computational biology , genetics , alternative splicing , human genetics , exon , phenotype , sequence (biology) , strengths and weaknesses , disease , genome , precision medicine , bioinformatics , gene , rna , philosophy , epistemology , medicine , pathology
Precision medicine and sequence‐based clinical diagnostics seek to predict disease risk or to identify causative variants from sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype‐phenotype prediction challenges; participants build models, undergo assessment, and share key findings. In the past, few CAGI challenges have addressed the impact of sequence variants on splicing. In CAGI5, two challenges (Vex‐seq and MaPSY) involved prediction of the effect of variants, primarily single‐nucleotide changes, on splicing. Although there are significant differences between these two challenges, both involved prediction of results from high‐throughput exon inclusion assays. Here, we discuss the methods used to predict the impact of these variants on splicing, their performance, strengths, and weaknesses, and prospects for predicting the impact of sequence variation on splicing and disease phenotypes.