kana review
A free, focused workspace for exploring and annotating single-cell data in a browser.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
kana is an open-source web application for researchers and biologists who want graphical tools for interactive single-cell omics analysis without installing desktop software. Its free plan runs computation in the browser using WebAssembly, so uploaded datasets remain on the user's device rather than being sent to a backend. The workflow is centered on single-cell preprocessing and exploration, making it a better fit for those tasks than for general statistical analysis.
Input support covers Matrix Market (.mtx), 10x HDF5, AnnData H5AD, and RDS files containing SummarizedExperiment or SingleCellExperiment objects, as well as Bioconductor ExperimentHub datasets. From there, users can apply quality filtering, normalization and log transformation, then use PCA, graph-based clustering, t-SNE or UMAP to inspect structure. Cluster marker detection, gene-set enrichment, reference-based cell-type annotation, MNN batch correction and multi-modal analysis extend the workflow beyond visualization. Interactive plots and export or reload of analysis state support continued exploration and sharing.
The published plan is Free, and the application is available on the web or self-hosted. Client-side execution is a meaningful fit when keeping datasets on the user's device matters; it also means the product is specifically organized around browser-based single-cell workflows rather than a general-purpose statistics environment. Documentation is the stated support channel. Researchers seeking a guided single-cell analysis path, with common data formats and standard analysis stages in one interface, should consider kana. Those who need broad statistical methods outside single-cell work should look for a more general tool.
kana pros and cons
- Where it wins
- Runs computations in the browser; datasets stay on the user's device
- Supports Matrix Market, 10x HDF5, H5AD and RDS inputs
- Combines clustering, embeddings, marker detection and annotation
- Where it doesn't
- Focused on single-cell analysis, not general statistical work
- Client-side computation may not suit every analysis environment
- Documentation is the listed support channel
kana fact sheet, pricing and score →
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