Dive into a comprehensive tutorial on performing pseudo-bulk differential expression analysis for single-cell RNA-Seq data using R. Learn the concept of pseudo-bulk analysis, its importance, and follow a detailed workflow to execute this approach. Explore data manipulation techniques using a Seurat object, including aggregating counts to sample level, and conduct differential expression analysis with DESeq2 to identify differentially expressed genes in specific cell type clusters. Gain hands-on experience with crucial steps such as fetching data from ExperimentHub, quality control, filtering, and implementing Seurat's standard workflow. Visualize your data, make informed decisions about integrated versus non-integrated data usage, and master essential data manipulation techniques. Conclude with a thorough walkthrough of DESeq2 analysis, from creating datasets to obtaining final results.