R-series

Your DESeq2 results table has thousands of rows, and sorting it in Excel tells you almost nothing about your experiment. Here is how to build volcano plots and MA plots in R with ggplot2 — and how to read what they are actually telling you.

You ran DESeq2 and got your list of differentially expressed genes. Now what? Here is how to use clusterProfiler to find out which biological pathways are actually changing in your experiment — with real code, real output, and real plots.

You already know R. Do you need Python too? An honest answer — plus a practical guide to getting your first Python environment running and your first biological data analyzed.

An honest head-to-head comparison of DESeq2 and edgeR. Learn the differences in their normalization, statistical tests, and run-times, and see if they actually give different biological answers.

Run DESeq2 on a real RNA-seq experiment, start to finish: load the airway dataset, filter low counts, model paired donors, and read the results table without fooling yourself.