"Seeing the Panel at Once" — Comparing Multiple Genes Across Your Cohort

 Research rarely lives at the level of a single gene for long. Within a few weeks of finding your gene of interest, you're building a panel — related family members, known interactors, upstream regulators, downstream targets. The question shifts from "what is this gene doing?" to "how does the whole set behave together?"

R2's Multiple Genes View is built for exactly this moment in a project.

Rather than clicking through each gene individually, you type a list — or paste it in from a spreadsheet — and R2 generates a side-by-side expression overview for all of them simultaneously. Each gene gets its own column of dots, arranged by sample, so you can scan across the panel and immediately see which genes are high, which are low, and crucially, whether they go up and down together or in opposition.

The track annotation system brings this to life. You split all samples by a clinical variable — tumour subtype, for instance — and suddenly each column of dots is colour-coded and grouped. You can see at a glance which genes in your panel are subtype-specific, which are uniformly expressed regardless of subtype, and which show the inverse pattern of the one next to them.

For those who prefer a more statistical summary, R2 also offers a bubble plot view: genes on one axis, sample groups on the other, with circle size indicating expression level and colour indicating whether the difference is statistically significant. It compresses a panel of a dozen genes across five tumour subtypes into a single, scannable figure that tells you immediately where the action is.

This view is particularly useful in two common lab situations. The first is the "family portrait" — you have a gene family and want to know which members matter in your disease context. The second is the "literature check" — a reviewer has asked whether your findings are specific to your gene or shared across its class. Either way, Multiple Genes View gives you the answer in minutes rather than days.

And because everything in R2 is connected, clicking on any gene in the overview takes you straight into the full single-gene analysis pipeline — so a panel overview naturally flows into individual deep-dives on the candidates that catch your eye.

This is Part of an ongoing series on the R2 Genomics Analysis and Visualization Platform, developed at Amsterdam UMC. All analyses can be freely performed at r2.amc.nl. Full tutorials at r2-tutorials.readthedocs.io.