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ZygosityPredictor.
Rheinnecker, Marco; Fröhlich, Martina; Rübsam, Marc; Paramasivam, Nagarajan; Heilig, Christoph E; Fröhling, Stefan; Schlenk, Richard F; Hutter, Barbara; Hübschmann, Daniel.
Afiliação
  • Rheinnecker M; Computational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
  • Fröhlich M; Computational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
  • Rübsam M; German Cancer Consortium (DKTK), 69120 Heidelberg, Germany.
  • Paramasivam N; Computational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
  • Heilig CE; Computational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
  • Fröhling S; German Cancer Consortium (DKTK), 69120 Heidelberg, Germany.
  • Schlenk RF; Division of Translational Medical Oncology, NCT Heidelberg and DKFZ, 69120 Heidelberg, Germany.
  • Hutter B; German Cancer Consortium (DKTK), 69120 Heidelberg, Germany.
  • Hübschmann D; Division of Translational Medical Oncology, NCT Heidelberg and DKFZ, 69120 Heidelberg, Germany.
Bioinform Adv ; 4(1): vbae017, 2024.
Article em En | MEDLINE | ID: mdl-38560552
ABSTRACT

Summary:

ZygosityPredictor provides functionality to evaluate how many copies of a gene are affected by mutations in next generation sequencing data. In cancer samples, the tool processes both somatic and germline mutations. In particular, ZygosityPredictor computes the number of affected copies for single nucleotide variants and small insertions and deletions (Indels). In addition, the tool integrates information at gene level via phasing of several variants and subsequent logic to derive how strongly a gene is affected by mutations and provides a measure of confidence. This information is of particular interest in precision oncology, e.g. when assessing whether unmutated copies of tumor-suppressor genes remain. Availability and implementation ZygosityPredictor was implemented as an R-package and is available via Bioconductor at https//bioconductor.org/packages/ZygosityPredictor. Detailed documentation is provided in the vignette including application to an example genome.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article