{Reference Type}: Journal Article
{Title}: RNA-Seq Data Analysis: A Practical Guide for Model and Non-Model Organisms.
{Author}: Pola-Sánchez E;Hernández-Martínez KM;Pérez-Estrada R;Sélem-Mójica N;Simpson J;Abraham-Juárez MJ;Herrera-Estrella A;Villalobos-Escobedo JM;
{Journal}: Curr Protoc
{Volume}: 4
{Issue}: 5
{Year}: 2024 May
暂无{DOI}: 10.1002/cpz1.1054
{Abstract}: RNA sequencing (RNA-seq) has emerged as a powerful tool for assessing genome-wide gene expression, revolutionizing various fields of biology. However, analyzing large RNA-seq datasets can be challenging, especially for students or researchers lacking bioinformatics experience. To address these challenges, we present a comprehensive guide to provide step-by-step workflows for analyzing RNA-seq data, from raw reads to functional enrichment analysis, starting with considerations for experimental design. This is designed to aid students and researchers working with any organism, irrespective of whether an assembled genome is available. Within this guide, we employ various recognized bioinformatics tools to navigate the landscape of RNA-seq analysis and discuss the advantages and disadvantages of different tools for the same task. Our protocol focuses on clarity, reproducibility, and practicality to enable users to navigate the complexities of RNA-seq data analysis easily and gain valuable biological insights from the datasets. Additionally, all scripts and a sample dataset are available in a GitHub repository to facilitate the implementation of the analysis pipeline. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Analysis of data from a model plant with an available reference genome Basic Protocol 2: Gene ontology enrichment analysis Basic Protocol 3: De novo assembly of data from non-model plants.