Shouib Rowayna, Eitzen Gary, Steenbergen Rineke
Faculty of Biotechnology, October University for Modern Sciences and Arts (MSA), Giza, Egypt.
Department of Cell Biology, University of Alberta, Edmonton, AB, Canada.
Bio Protoc. 2025 May 5;15(9):e5295. doi: 10.21769/BioProtoc.5295.
RNA sequencing (RNA-Seq) has transformed transcriptomic research, enabling researchers to perform large-scale inspection of mRNA levels in living cells. With the growing applicability of this technique to many scientific investigations, the analysis of next-generation sequencing (NGS) data becomes an important yet challenging task, especially for researchers without a bioinformatics background. This protocol offers a beginner-friendly step-by-step guide to analyze NGS data (starting from raw .fastq files), providing the required codes with an explanation of the different steps and software used. We outline a computational workflow that includes quality control, trimming of reads, read alignment to the genome, and gene quantification, ultimately enabling researchers to identify differentially expressed genes and gain insights on mRNA levels. Multiple approaches to visualize this data using statistical and graphical tools in R are also described, allowing the generation of heatmaps and volcano plots to represent genes and gene sets of interest. Key features • Provides a beginner-friendly protocol for RNA-Seq analysis to obtain insights into gene expression. • Pipeline starts with raw .fastq files and involves analysis in command line/terminal and R (via RStudio). • Yields a variety of output files that represent mRNA levels amongst different samples. Output files include count files, heatmaps, ordered lists of DEGs, and volcano plots.
RNA测序（RNA-Seq）已经改变了转录组学研究，使研究人员能够对活细胞中的mRNA水平进行大规模检测。随着这项技术在许多科学研究中的应用越来越广泛，下一代测序（NGS）数据的分析成为一项重要但具有挑战性的任务，尤其是对于没有生物信息学背景的研究人员而言。本方案提供了一个对初学者友好的逐步指南，用于分析NGS数据（从原始的.fastq文件开始），提供所需的代码，并对不同步骤和使用的软件进行解释。我们概述了一个计算工作流程，包括质量控制、读段修剪、读段与基因组比对以及基因定量，最终使研究人员能够识别差异表达基因并深入了解mRNA水平。还描述了使用R中的统计和图形工具可视化这些数据的多种方法，从而生成热图和火山图来表示感兴趣的基因和基因集。关键特性 • 提供一个对初学者友好的RNA-Seq分析方案，以深入了解基因表达。 • 流程从原始的.fastq文件开始，涉及在命令行/终端和R（通过RStudio）中进行分析。 • 生成各种表示不同样本中mRNA水平的输出文件。输出文件包括计数文件、热图、差异表达基因的有序列表和火山图。
