Ilnytskyy Slava, Bilichak Andriy
Department of Biological Sciences, University of Lethbridge, 4401 University Drive, Lethbridge, AB, Canada, T1K 3M4.
Agriculture and Agri-Food Canada, Lethbridge Research Centre, Lethbridge, AB, Canada.
Methods Mol Biol. 2017;1456:197-224. doi: 10.1007/978-1-4899-7708-3_16.
Next-generation sequencing became a method of choice for the investigation of small RNA transcriptomes in plants and animals. Although a technical side of sequencing itself is becoming routine, and experimental costs are affordable, data analysis still remains a challenge, especially for researchers with limited computational experience. Here, we present a detailed description of a computational workflow designed to take raw sequencing reads as input, to obtain small RNA predictions, and to detect the differentially expressed microRNAs as a result. The exact commands and pieces of code are provided and hopefully can be adapted and used by other researchers to facilitate the study of small RNA regulation.
下一代测序已成为研究动植物小RNA转录组的首选方法。尽管测序本身的技术层面已日趋常规，且实验成本也在可承受范围内，但数据分析仍然是一项挑战，对于计算经验有限的研究人员而言尤其如此。在此，我们详细描述了一种计算工作流程，该流程以原始测序读数为输入，以获得小RNA预测结果，并最终检测出差异表达的微小RNA。文中提供了确切的命令和代码片段，希望其他研究人员能够对其进行调整和使用，以促进小RNA调控的研究。
