Your browser doesn't support javascript.
loading
ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations.
Renaux, Alexandre; Papadimitriou, Sofia; Versbraegen, Nassim; Nachtegael, Charlotte; Boutry, Simon; Nowé, Ann; Smits, Guillaume; Lenaerts, Tom.
  • Renaux A; Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Papadimitriou S; Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium.
  • Versbraegen N; Artificial Intelligence lab, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Nachtegael C; Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Boutry S; Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium.
  • Nowé A; Artificial Intelligence lab, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Smits G; Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Lenaerts T; Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium.
Nucleic Acids Res ; 47(W1): W93-W98, 2019 07 02.
Article en En | MEDLINE | ID: mdl-31147699
ABSTRACT
A tremendous amount of DNA sequencing data is being produced around the world with the ambition to capture in more detail the mechanisms underlying human diseases. While numerous bioinformatics tools exist that allow the discovery of causal variants in Mendelian diseases, little to no support is provided to do the same for variant combinations, an essential task for the discovery of the causes of oligogenic diseases. ORVAL (the Oligogenic Resource for Variant AnaLysis), which is presented here, provides an answer to this problem by focusing on generating networks of candidate pathogenic variant combinations in gene pairs, as opposed to isolated variants in unique genes. This online platform integrates innovative machine learning methods for combinatorial variant pathogenicity prediction with visualization techniques, offering several interactive and exploratory tools, such as pathogenic gene and protein interaction networks, a ranking of pathogenic gene pairs, as well as visual mappings of the cellular location and pathway information. ORVAL is the first web-based exploration platform dedicated to identifying networks of candidate pathogenic variant combinations with the sole ambition to help in uncovering oligogenic causes for patients that cannot rely on the classical disease analysis tools. ORVAL is available at https//orval.ibsquare.be.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Predisposición Genética a la Enfermedad / Herencia Multifactorial / Enfermedades Genéticas Congénitas Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Predisposición Genética a la Enfermedad / Herencia Multifactorial / Enfermedades Genéticas Congénitas Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article