Wang Xin, He Siyu, Li Jian, Wang Jun, Wang Chengyi, Wang Mingwei, He Danni, Lv Xingfeng, Zhong Qiuyan, Wang Hongjiu, Wang Zhenzhen
College of Bioinformatics Science and Technology, Harbin Medical University, Heilongjiang, China.
College of Computer Science and Technology, Heilongjiang University, Harbin, China.
PeerJ. 2020 Jul 8;8:e9371. doi: 10.7717/peerj.9371. eCollection 2020.
The life cycle of intracellular RNA mainly involves transcriptional production, splicing maturation and degradation processes. Their dynamic changes are termed as RNA life cycle dynamics (RLCD). It is still challenging for the accurate and robust identification of RLCD under unknow the functional form of RLCD. By using the pulse model, we developed an R package named pulseTD to identify RLCD by integrating 4sU-seq and RNA-seq data, and it provides flexible functions to capture continuous changes in RCLD rates. More importantly, it also can predict the trend of RNA transcription and expression changes in future time points. The pulseTD shows better accuracy and robustness than some other methods, and it is available on the GitHub repository (https://github.com/bioWzz/pulseTD_0.2.0).
细胞内RNA的生命周期主要涉及转录产生、剪接成熟和降解过程。它们的动态变化被称为RNA生命周期动态（RLCD）。在未知RLCD功能形式的情况下，准确且稳健地识别RLCD仍然具有挑战性。通过使用脉冲模型，我们开发了一个名为pulseTD的R包，通过整合4sU-seq和RNA-seq数据来识别RLCD，并且它提供了灵活的功能来捕捉RCLD速率的连续变化。更重要的是，它还可以预测未来时间点RNA转录和表达变化的趋势。pulseTD比其他一些方法表现出更好的准确性和稳健性，并且可以在GitHub仓库（https://github.com/bioWzz/pulseTD_0.2.0）上获取。
