We’ve added two new ways to explore high-dimensional cytometry data, now available across Population Counts (Absolute Cell Counts), Population Frequencies, Functional Markers, and Marker Expression tabs in the Immune Changes section:
1. Grouped Heatmap
- What it shows: The average value for each cell population, functional marker subset, or marker expression level for every study endpoint you select (e.g., baseline, on-treatment, or dose groups).
- When to use it: Quickly compare immune cell population averages across groups to see how treatment, dose, or other variables affect them.
2. Correlation Heatmap
- What it shows: How strongly two populations, functional subsets, or markers are related within a cohort. Positive values mean they tend to increase together; negative values mean they tend to move in opposite directions.
- When to use it: Spot coordinated immune responses or trade-offs between cell populations in a single group.
Making the Data Even Clearer: Heatmaps Normalization
We didn’t stop at visualization. We added Heatmap Normalization so you can control how your data is scaled and compared:
- Raw Values for absolute abundances.
- Fold Change or Log2 Fold Change vs. a baseline for symmetric, interpretable shifts.
- Percent Change for a straightforward, linear view.
Available Now
Heatmap Views with normalization is now available today for all Teiko Dashboard users.
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