A single experiment is a data point. Its meaning almost always emerges in context: next to other studies, other conditions, other modalities. That's the whole premise of meta-analysis, and it's an area we've invested heavily in this release.
Combine your data with curated references
You can now include Library experiments directly in a meta-analysis, combining your own data with curated reference datasets in one analysis. That's a meaningful shift: your experiment stops being an island and starts being part of a larger conversation, measured against a growing body of reference data rather than in isolation.
Sharper, faster, more flexible
- Building a meta-analysis is faster, with streamlined experiment selection and cluster configuration.
- You can select gene lists from Gene List Manager when configuring a cluster, so your curated gene sets drive the comparison.
- You can run meta-analyses on single clusters with modified annotations, for focused, targeted contrasts.
- The results page reads more clearly, with improved hypersummary display and heatmap rendering.
Now spanning modalities
Perhaps the most exciting part: GeoMx DSP spatial experiments can now join meta-analyses alongside your bulk and single-cell data. Multiomic, cross-modality integration is one of the defining trends in the field right now: the recognition that no single assay tells the whole story. Bringing spatial into the same analytical frame as everything else is a real step toward that.
And to make all this practical at scale, large exports now stream directly from storage, so multi-gigabyte downloads finish reliably instead of timing out. The more your data connects to other data, the more valuable each experiment becomes. That's not a small idea. It's a mindset shift we've been building toward for a while: from analyzing experiments one at a time to treating a growing, curated body of data as a single, queryable resource. Meta-analysis is where that shift becomes tangible, and building the place where all those connections live is exactly where we want Rosalind to be.
.png)
