Rheinnecker Marco, Fröhlich Martina, Rübsam Marc, Paramasivam Nagarajan, Heilig Christoph E, Fröhling Stefan, Schlenk Richard F, Hutter Barbara, Hübschmann Daniel
Computational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
German Cancer Consortium (DKTK), 69120 Heidelberg, Germany.
Bioinform Adv. 2024 Feb 6;4(1):vbae017. doi: 10.1093/bioadv/vbae017. eCollection 2024.
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.
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.
ZygosityPredictor提供了一种功能，用于评估下一代测序数据中的突变影响了基因的多少个拷贝。在癌症样本中，该工具可处理体细胞突变和种系突变。特别是，ZygosityPredictor可计算单核苷酸变异以及小插入和缺失（Indels）的受影响拷贝数。此外，该工具通过对多个变异进行定相并随后运用逻辑来整合基因水平的信息，以得出基因受突变影响的程度，并提供一个置信度度量。此信息在精准肿瘤学中尤为重要，例如在评估肿瘤抑制基因的未突变拷贝是否仍然存在时。
ZygosityPredictor被实现为一个R包，可通过生物导体（Bioconductor）在https://bioconductor.org/packages/ZygosityPredictor获取。在 vignette 中提供了详细的文档，包括对一个示例基因组的应用。
