November 18, 2010  |  Announcements  |  By  |  1 Comment

View Through a Heatmap: Have Your Cake and Eat It Too

Dataset #310: Phospho-Flow Cytokine Titration

Q: I want a big picture view of my flow cytometry experiment so that I can see how all of my samples are behaving under different conditions. But I also want to see the underlying single cell details because subsets of cells in these samples may be responding differently. Is this possible?

A: Absolutely. You can have your cake and eat it too by using a built-in feature on Cytobank to view-through a heatmap representation of your data.

Let’s illustrate with an example. Login to Cytobank and open a public experiment called “Phospho-Flow Cytokine Titration”. This experiment is an example titration of a cytokine (IL-2) using healthy human peripheral blood. The associated phospho-protein p-Stat5 was measured, as were the cell surface markers CD3, CD4, and CD8.

In order to interact with the data, you’ll need to clone the experiment. Under Illustrations, click on “Heatmap view of IL-2 signaling”. This action makes the heatmap illustration your working illustration and allows you to interact with it.

As we can see below, the heatmap gives us a quick overview of how p-Stat5 levels change in response to IL-2 stimulation and whether that change is different between the donors. We can see, for example, that the blood cells from Donor 1 are more sensitive to IL-2 stimulation than cells from Donor 2. They show a higher fold change in p-Stat5 levels at all concentrations.

Mousing over an individual square of the heatmap gives us a view of the underlying data used to generate the statistic in that square. In this case, the view-through plots are 2D density dot plots of FITC (CD4) vs. Alexa 647 (p-Stat5). Mousing over the square that represents Donor 1 cells treated with 0.16 ng/ml IL-2 shows us that the CD4+ cells are more sensitive to cytokine stimulation than CD4- cells.

By only looking at the heatmap, we might not realize that there are two populations with very different responses contributing to that single square. The view-through reveals heterogeneity and shows the power of flow cytometry to identify cell subpopulations.

A more detailed walk-through of the data analysis is available in Current Protocols in Cytometry. Questions? Contact us at

– Jonathan and Stephanie

Reference: Kotecha N, Krutzik PO, Irish JM. Web-based analysis and publication of flow cytometry experiments. Current Protocols in Cytometry. 2010. 53:10.17.1–10.17.24. PMID: 20578106