In this video, we continue the RNA-seq workflow and move into the downstream analysis stage using the count matrix generated from the previous steps.
This part covers:
* DESeq2 setup and package installation
* reading the FeatureCounts count table
* filtering low-count genes
* normalization of RNA-seq counts
* summary statistics
* exploratory data analysis
* expression distribution plots
* heatmaps
* ranked and cumulative expression plots
* interpretation of normalized RNA-seq outputs
This video is designed to help beginners understand how RNA-seq count data is transformed into interpretable biological results. It is not focused on differential expression between multiple groups yet. Instead, the goal is to build a strong foundation in normalization and exploratory transcriptomic analysis.
In the next video, we will move into sample comparison and directly look at comparison results.
If you find educational videos like this useful, please support them. These tutorials take a lot of time, troubleshooting, and effort to prepare, and the goal is to share knowledge in a practical way.
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