SpliceAI-visual: a free online tool to improve SpliceAI splicing variant interpretation

被引:68
作者
Agathe, Jean-Madeleine de Sainte [1 ,2 ]
Filser, Mathilde [1 ]
Isidor, Bertrand [3 ]
Besnard, Thomas [3 ]
Gueguen, Paul [2 ,4 ]
Perrin, Aurelien [5 ]
Van Goethem, Charles [5 ]
Verebi, Camille [6 ]
Masingue, Marion [7 ]
Rendu, John [8 ]
Cossee, Mireille [5 ,9 ]
Bergougnoux, Anne [5 ,9 ]
Frobert, Laurent [2 ]
Buratti, Julien [1 ]
Lejeune, Elodie [1 ]
Le Guern, Eric [1 ,2 ]
Pasquier, Florence [10 ]
Clot, Fabienne [1 ]
Kalatzis, Vasiliki [11 ]
Roux, Anne-Francoise [5 ,12 ]
Cogne, Benjamin [2 ,3 ]
Baux, David [5 ,12 ]
机构
[1] Sorbonne Univ, Lab Medecine Genomique Sorbonne Univ, Dept Genet Medicale, AP HP,Grp Hospitalier Univ Pitie Salpetriere, Paris, France
[2] Lab Biol Medicale Multis SeqOIA Lab seqoia fr, Paris, France
[3] Nantes Univ, CHU Nantes, Serv Genet Medicale, F-44000 Nantes, France
[4] CHRU Tours, Serv Genet, Inserm U1253, Tours, France
[5] Univ Montpellier, CHU Montpellier, Lab Genet Mol, Montpellier, France
[6] Univ Paris Cite, Hop Cochin, APHP Ctr, DMU BioPhyGen,Serv Medecine Genomique ,Malad Syst, Paris, France
[7] Hop La Pitie Salpetriere, Ctr reference Malad neuromusculaires Nord Est Ile, APHP, Paris, France
[8] Univ Grenoble Alpes, Grenoble Inst Neurosci, Inserm, U1216,CHU Grenoble, Grenoble, France
[9] Univ Montpellier, PhyMedExp, INSERM, CNRS, Montpellier, France
[10] Univ Lille, Ctr memoire, Inserm DistALZ U1172, Licend,CHU Lille, F-59000 Lille, France
[11] Univ Montpellier, INM, INSERM, Montpellier, France
[12] Univ Montpellier, INM, INSERM, CHU Montpellier, Montpellier, France
关键词
GENE; MUTATIONS; FREQUENT; GENOMICS;
D O I
10.1186/s40246-023-00451-1
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ().
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页数:16
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