R

Your qPCR run is done and you have a column of Ct values. Here is how to turn them into fold changes with the ΔΔCt method, worked by hand, in a spreadsheet and in R, plus the mistakes that get qPCR figures sent back by reviewers.

A five-person molecular biology lab easily spends $6,000 a year on per-seat subscriptions for Prism, SnapGene, FlowJo, and BioRender. I tested the free, open-source replacements on real bench data — from 4PL IC50 curves and diagnostic digests to FCS gating — and looked honestly at where the free stack wins and where it still hurts.

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.

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.