ifCNV: A novel isolation-forest-based package to detect copy-number variations from various targeted NGS datasets.

Cabello-Aguilar, Simon; Vendrell, Julie A; Van Goethem, Charles; Brousse, Mehdi; Gozé, Catherine; Frantz, Laurent; Solassol, Jérôme

Cabello-Aguilar, Simon; Vendrell, Julie A; Van Goethem, Charles; Brousse, Mehdi; Gozé, Catherine; Frantz, Laurent; Solassol, Jérôme.

Afiliação

Cabello-Aguilar S; Laboratoire de Biologie des Tumeurs Solides, Département de Pathologie et Oncobiologie, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France.
Vendrell JA; Laboratoire de Biologie des Tumeurs Solides, Département de Pathologie et Oncobiologie, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France.
Van Goethem C; Laboratoire de Génétique Moléculaire, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France.
Brousse M; Laboratoire d'Hématologie Biologique, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France.
Gozé C; Laboratoire de Biologie des Tumeurs Solides, Département de Pathologie et Oncobiologie, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France.
Frantz L; Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University of Munich, Munich, Germany.
Solassol J; School of Biological and Chemical Sciences, Queen Mary University of London, London, UK.

Mol Ther Nucleic Acids ; 30: 174-183, 2022 Dec 13.

Article em En | MEDLINE | ID: mdl-36250203

Palavras-chave

CNV detection; MT: Bioinformatics; Python open-source package; R open-source package; artificial intelligence; localization scoring; machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Mol Ther Nucleic Acids Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França País de publicação: Estados Unidos

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