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A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity

SUMMARY: Assessing the pathogenicity of genetic variants can be a complex and challenging task. Spliceogenic variants, which alter mRNA splicing, may yield mature transcripts that encode non-functional protein products, an important predictor of Mendelian disease risk. However, most variant annotati...

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Detalles Bibliográficos
Autores principales: Shamsani, Jannah, Kazakoff, Stephen H, Armean, Irina M, McLaren, Will, Parsons, Michael T, Thompson, Bryony A, O’Mara, Tracy A, Hunt, Sarah E, Waddell, Nicola, Spurdle, Amanda B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6596880/
https://www.ncbi.nlm.nih.gov/pubmed/30475984
http://dx.doi.org/10.1093/bioinformatics/bty960
Descripción
Sumario:SUMMARY: Assessing the pathogenicity of genetic variants can be a complex and challenging task. Spliceogenic variants, which alter mRNA splicing, may yield mature transcripts that encode non-functional protein products, an important predictor of Mendelian disease risk. However, most variant annotation tools do not adequately assess spliceogenicity outside the native splice site and thus the disease-causing potential of variants in other intronic and exonic regions is often overlooked. Here, we present a plugin for the Ensembl Variant Effect Predictor that packages MaxEntScan and extends its functionality to provide splice site predictions using a maximum entropy model. The plugin incorporates a sliding window algorithm to predict splice site loss or gain for any variant that overlaps a transcript feature. We also demonstrate the utility of the plugin by comparing our predictions to two mRNA splicing datasets containing several cancer-susceptibility genes. AVAILABILITY AND IMPLEMENTATION: Source code is freely available under the Apache License, Version 2.0: https://github.com/Ensembl/VEP_plugins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.