Guo Zhihao, Ni Ying, Tan Lu, Shao Yanwen, Ye Lianwei, Chen Sheng, Li Runsheng
Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.
Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong, China.
NAR Genom Bioinform. 2024 May 20;6(2):lqae052. doi: 10.1093/nargab/lqae052. eCollection 2024 Jun.
Nanopore sequencing technologies have enabled the direct detection of base modifications in DNA or RNA molecules. Despite these advancements, the tools for visualizing electrical current, essential for analyzing base modifications, are often lacking in clarity and compatibility with diverse nanopore pipelines. Here, we present Nanopore Current Events Magnifier (nanoCEM, https://github.com/lrslab/nanoCEM), a Python command-line tool designed to facilitate the identification of DNA/RNA modification sites through enhanced visualization and statistical analysis. Compatible with the four preprocessing methods including 'f5c resquiggle', 'f5c eventalign', 'Tombo' and 'move table', nanoCEM is applicable to RNA and DNA analysis across multiple flow cell types. By utilizing rescaling techniques and calculating various statistical features, nanoCEM provides more accurate and comparable visualization of current events, allowing researchers to effectively observe differences between samples and showcase the modified sites.
纳米孔测序技术已能够直接检测DNA或RNA分子中的碱基修饰。尽管有这些进展,但用于可视化电流(这对分析碱基修饰至关重要)的工具往往清晰度不足,且与各种纳米孔流程不兼容。在此,我们展示了纳米孔电流事件放大器(nanoCEM,https://github.com/lrslab/nanoCEM),这是一个Python命令行工具,旨在通过增强可视化和统计分析来促进DNA/RNA修饰位点的识别。nanoCEM与包括“f5c重新比对”、“f5c事件对齐”、“Tombo”和“移动表格”在内的四种预处理方法兼容,适用于多种流动池类型的RNA和DNA分析。通过利用重缩放技术并计算各种统计特征,nanoCEM提供了更准确且可比的电流事件可视化,使研究人员能够有效观察样本之间的差异并展示修饰位点。