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REVIEW article

Front. Genet.

Sec. Computational Genomics

Volume 16 - 2025 | doi: 10.3389/fgene.2025.1697922

From bench to bytes: A practical guide to RNA sequencing data analysis

Provisionally accepted
  • Department of Biology, University of Mississippi, Oxford, United States

The final, formatted version of the article will be published soon.

RNA sequencing (RNA-Seq) is a high-throughput sequencing approach that enables comprehensive quantification of transcriptomes at a genome-wide scale. As a result, RNA-Seq has become a routine component of molecular biology research, and more researchers are now expected to analyze RNA-Seq data as part of their projects. However, unlike the largely experimental nature of benchwork, RNA-Seq analysis demands proficiency with computational and statistical approaches to manage technical issues and large data sizes. Although numerous manuals and reviews on RNA-Seq data analysis are available, many are either highly specialized, fragmented, or overly superficial, leaving beginners to use tools without understanding the underlying principles. To address this gap, we provide a decision-oriented guide tailored for molecular biologists encountering RNA-Seq analysis for the first time. This review is designed for readers enable to decide which tools and statistical approaches to use based on their data, goals, and constraints. We aim to equip beginners with the knowledge required to perform RNA-Seq analysis rigorously and with confidence.

Keywords: Beginner's guide, bioinformatics, DESeq2, gene expression analysis, RNA-Seq

Received: 02 Sep 2025; Accepted: 13 Oct 2025.

Copyright: © 2025 Dawadi, Pokharel, Shrestha, Niraula, Naeem, Miura, Roy and Nepal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Mishal Roy, mishalroy0@gmail.com
Saroj Nepal, snepal1@go.olemiss.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.