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Single-cell profiling has gone from heroic to routine in just a few years. That's wonderful for biology, and hard on visualization. When an experiment has dozens of samples and clusters, a scatter plot can turn into a wall of overlapping dots, and the subtle population you're chasing gets lost in the crowd. This release is a set of focused upgrades aimed squarely at that problem.
Isolate the biology you care about
You can now toggle individual samples on and off in single-cell scatter plots. Want to see how one condition sits relative to the rest, or pull a single donor out of a busy plot? Turn the others off and look. It's a small interaction that changes how quickly you can reason about a subset.
Colors you can actually tell apart
Crowded plots live and die by their palette. We've expanded the color palette with more distinguishable colors, so experiments with many samples or clusters stay readable instead of blurring into similar hues. And MDS plots now support up to 50 variables, giving you a richer, higher-dimensional view of how your samples relate at a glance.
Small touches that add up
The single-cell download-plots panel now includes a scroll bar, so export buttons stay reachable even on smaller screens, the kind of detail you only notice when it's missing.
Exploration is where single-cell discovery actually happens: the moment you notice a cluster behaving oddly, or two conditions separating in a way you didn't expect. The clearer that view, the faster the insight, and the better the questions you ask next. It's also part of a steady deepening of our data-science work: as we bring more data types into one rigorous home and sharpen how you see them, each experiment starts to inform the next, and the whole becomes worth more than the sum of its parts. That's what these changes are for.
