Ye Wenbin, Liu Tao, Fu Hongjuan, Ye Congting, Ji Guoli, Wu Xiaohui
Department of Automation, Xiamen University, Xiamen 361005, China.
Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China.
Bioinformatics. 2021 Aug 25;37(16):2470-2472. doi: 10.1093/bioinformatics/btaa997.
Alternative polyadenylation (APA) has been widely recognized as a widespread mechanism modulated dynamically. Studies based on 3' end sequencing and/or RNA-seq have profiled poly(A) sites in various species with diverse pipelines, yet no unified and easy-to-use toolkit is available for comprehensive APA analyses.
We developed an R package called movAPA for modeling and visualization of dynamics of alternative polyadenylation across biological samples. movAPA incorporates rich functions for preprocessing, annotation and statistical analyses of poly(A) sites, identification of poly(A) signals, profiling of APA dynamics and visualization. Particularly, seven metrics are provided for measuring the tissue-specificity or usages of APA sites across samples. Three methods are used for identifying 3' UTR shortening/lengthening events between conditions. APA site switching involving non-3' UTR polyadenylation can also be explored. Using poly(A) site data from rice and mouse sperm cells, we demonstrated the high scalability and flexibility of movAPA in profiling APA dynamics across tissues and single cells.
https://github.com/BMILAB/movAPA.
Supplementary data are available at Bioinformatics online.
可变聚腺苷酸化(APA)已被广泛认为是一种受到动态调控的普遍机制。基于3'端测序和/或RNA测序的研究已经使用各种流程对不同物种中的聚腺苷酸化位点进行了分析,然而目前还没有一个统一且易于使用的工具包可用于全面的APA分析。
我们开发了一个名为movAPA的R包,用于对生物样本间可变聚腺苷酸化的动态变化进行建模和可视化。movAPA包含了丰富的功能,用于聚腺苷酸化位点的预处理、注释和统计分析、聚腺苷酸化信号的识别、APA动态变化的分析以及可视化。特别地,提供了七个指标来衡量样本间APA位点的组织特异性或使用情况。使用三种方法来识别不同条件之间的3'UTR缩短/延长事件。还可以探索涉及非3'UTR聚腺苷酸化的APA位点切换。利用来自水稻和小鼠精子细胞的聚腺苷酸化位点数据,我们证明了movAPA在分析跨组织和单细胞的APA动态变化方面具有高扩展性和灵活性。
https://github.com/BMILAB/movAPA。
补充数据可在《生物信息学》在线获取。