Cirrocumulus for Single-Cell Data Visualization

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

  • Run 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 to explore relationships between categorical variables and expression

  • Interactively create and share “AND” or “OR” filters

  • Collaboratively annotate cell types in real time

  • Quickly load multiple features from predefined lists

  • 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

  • Visualize STAR-Fusion results alongside single cell expression

Quick Start

Install the package:

pip install cirrocumulus

Launch cirrocumulus via the command line:

cirro launch <path_to_dataset>
  • Datasets can be provided in h5ad, loom or STAR-Fusion format. Seurat objects can be loaded after converting to h5ad or loom format (see vignette).

  • 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.

  • Predefined marker lists can be provided in JSON format (see example) to quickly browse features of interest.

Example Data