This tutorial is based on Bioconductor packages, RNAseq gene differential expression analysis, including filtering, preprocessing, visualization, clustering, and Enrichment. In case you have any queries or questions, please feel free to ask or correct. I hope it will be useful for new Bioconductor users.
Required data files You should have a raw count and annotation/metadata file for running this analysis (In this tutorial example files are provided). Raw count files are usually obtained from tools such as featureCount, RSem, etc from Bam files.
Bioconductor packages to be installed
biomaRt (Useful for gene filtering and annotations)
PCAtools (PCA detailed analysis)
ReactomePA (enrichment analysis)
Note: PCA and Enrichment analysis is based on Deseq2. However, users may be interested in considering only those genes that are commonly differentially expressed between DEseq2 and EdgeR.
R script and further instructions of the tutorial are available here.