Showing content from https://github.com/lilab-bcb/cirrocumulus below:
lilab-bcb/cirrocumulus: Bring your single-cell data to life
Cirrocumulus is an interactive visualization tool for large-scale single-cell genomics data, with the following features:
- Visualize datasets in h5ad, 10x h5, Xenium, loom, Seurat, TileDB, or zarr formats
- View MERFISH or other spatial transcriptomics data overlaid on an image
- Easily deploy on a laptop, on-premise server, cloud VM, or Google App Engine
- Share the current visualization state in a URL
- Share datasets securely with collaborators
- Create dotplots, heatmaps, and violin plots to explore relationships between categorical variables and expression
- Generate composition plots to inspect cluster makeup
- Explore complete differential expression results generated by Scanpy or Pegasus/Cumulus
- Interactively create and share “AND” or “OR” filters
- Collaboratively annotate cell types in real time, optionally using a controlled vocabulary (example ontology)
- Quickly load multiple features from predefined lists (see example)
- Explore multiple features and embeddings simultaneously
- Fast interactive exploration of 2 and 3-d embeddings of millions of cells, including zoom, pan, rotate (3-d), and lasso tools
- Save publication quality images
- Highly customizable - for example, set the color map, point size, or whether to use fog for 3-d embeddings to fade distant points
Install the package:
pip install cirrocumulus
Launch cirrocumulus via the command line:
cirro launch <path_to_dataset>
- Launch accepts more than one dataset to enable quick dataset switching or to combine modalities (e.g gene fusions and expression) stored in separate files.
Complete documentation available at https://cirrocumulus.readthedocs.io
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