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Single-cell visualization application

Project description

Cirrocumulus

Cirrocumulus is an interactive visualization tool for large-scale single-cell genomics data, with the following features:

  • Easily deploy on a laptop, on-premise server, cloud VM, or Google App Engine

  • View spatial transcriptomics data overlaid on an image

  • 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)

  • 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

  • Visualize datasets in h5ad, loom, Seurat, TileDB, zarr, or STAR-Fusion formats

  • Highly customizable - for example, set the color map, point size, or whether to use fog for 3-d embeddings to fade distant points

Quick Start

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.

Example Data

Complete documentation available at https://cirrocumulus.readthedocs.io

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