Abstract：
Immunofluorescent staining is commonly used to generate images to characterize cytological phenotypes. The manual quantification of DNA double-strand breaks and their repair intermediates during meiosis using image data requires a series of subjective steps, from image selection to the counting of particular events per nucleus. Here we describe \"synapsis,\" a bioconductor package, which includes a set of functions to automate the process of identifying meiotic nuclei and quantifying key double-strand break formation and repair events in a rapid, scalable, and reproducible workflow, and compare it to manual user quantification. The software can be extended for other applications in meiosis research, such as incorporating machine learning approaches to categorize meiotic substages.
摘要：
免疫荧光染色通常用于生成图像以表征细胞学表型。使用图像数据对减数分裂过程中的DNA双链断裂及其修复中间体进行手动定量需要一系列主观步骤，从图像选择到每个细胞核特定事件的计数。在这里我们描述“突触，“一个生物导体包，其中包括一组功能，以自动识别减数分裂细胞核和定量关键的双链断裂形成和修复事件的过程，可扩展，和可重复的工作流程，并将其与手动用户量化进行比较。该软件可以扩展到减数分裂研究中的其他应用，例如结合机器学习方法对减数分裂子进行分类。
