BRCA1 基因启动子内的低水平嵌合表突变发生在 5-8% 的健康个体中，并且与乳腺癌和卵巢癌的风险显着升高相关。类似的事件也可能影响其他肿瘤抑制基因，可能是癌症负担的重要贡献者。虽然这为转化研究开辟了一个新领域，但低水平嵌合表观遗传事件的检测需要高度灵敏和稳健的甲基化分析方法。我们在此介绍 epialleleR，这是一种计算框架，用于甲基化测序数据中镶嵌表观突变的灵敏检测、定量和可视化。通过分析模拟和真实数据集，我们提供了表观等位基因性能的深入评估，并表明与表观单倍型数据的联系对于检测低水平甲基化事件是必要的。 epialleleR 可作为开源 R/Bioconductor 包在 https://github.com/BBCG/epialleR 和 https://bioconductor.org/packages/epialleR/ 上免费获取。© 作者 2023。出版者牛津大学出版社 GigaScience。

Low-level mosaic epimutations within the BRCA1 gene promoter occur in 5-8% of healthy individuals and are associated with a significantly elevated risk of breast and ovarian cancer. Similar events may also affect other tumor suppressor genes, potentially being a significant contributor to cancer burden. While this opens a new area for translational research, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis. We here present epialleleR, a computational framework for sensitive detection, quantification, and visualization of mosaic epimutations in methylation sequencing data. Analyzing simulated and real data sets, we provide in-depth assessments of epialleleR performance and show that linkage to epihaplotype data is necessary to detect low-level methylation events. The epialleleR is freely available at https://github.com/BBCG/epialleleR and https://bioconductor.org/packages/epialleleR/ as an open-source R/Bioconductor package.© The Author(s) 2023. Published by Oxford University Press GigaScience.