A Guide to Basic RNA Sequencing Data Processing and Transcriptomic Analysis.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• RNA sequencing (RNA-Seq) is a powerful technique for analyzing mRNA levels in cells.
• Analyzing next-generation sequencing (NGS) data presents challenges, particularly for those without bioinformatics expertise.
• Standardized protocols are needed to make RNA-Seq analysis accessible.

Purpose of the Study:

• To provide a beginner-friendly, step-by-step protocol for analyzing RNA-Seq data.
• To guide researchers through the computational workflow from raw .fastq files to gene expression insights.
• To enable the identification and visualization of differentially expressed genes (DEGs).

Main Methods:

• The protocol details a computational workflow including quality control, read trimming, and genome alignment.
• It covers gene quantification to determine mRNA levels across samples.
• Data visualization using R, including heatmaps and volcano plots, is explained.

Main Results:

• The workflow yields essential output files such as count files and lists of DEGs.
• Researchers can generate heatmaps and volcano plots for visualizing gene expression patterns.
• The protocol facilitates a comprehensive understanding of mRNA levels and gene sets.

Conclusions:

• This protocol democratizes RNA-Seq data analysis for researchers lacking bioinformatics backgrounds.
• It empowers scientists to gain meaningful insights into gene expression from NGS data.
• The described methods and visualizations aid in interpreting transcriptomic research findings.