Multiomics Python package
Analyze Spatial Data Objects from Cytos cell screening runs with the multiomics Python package.
The multiomics Python package is the Element Biosciences Python library for loading, quality-checking, and analyzing Spatial Data Objects (SDOs) from AVITI24™ Cytos™ cell screening runs. It runs on a laptop, HPC cluster, or cloud environment, with or without an agent. Pair it with the multiomics skills for agent-guided analysis.
The installable package is elembio-spatialdata-analysis. In Python, import it as ebsd.
What you can do
- Load SDOs from a local zip archive, directory, or S3
- Inspect available tables and modalities for a run
- Filter, normalize, and quality-check cells and runs
- Prepare tables for Scanpy and other AnnData tools for clustering and differential expression
- Plot QC distributions, well images, and individual cells
Which assays are present depends on how the run was configured (for example, 3′ transcriptome, OPS, and imaging). Discover available tables before choosing an analysis path.
How it fits
- Each cell screening run produces an SDO (
RunID.zarr.zip) and visualization outputs. The SDO comes from on-instrument analysis on the AVITI24 System, the multiomics workflow, or a standalone Cells2Stats run. - The multiomics Python package loads that SDO and runs analysis in Python.
- Optionally, the multiomics skills in the Agent Hub guide an agent to call the same package.
- Plot imagery and overlays in Python with the multiomics Python package, or explore the run in CytoCanvas Desktop or CytoCanvas Studio.
Start here
Tutorials
- Clustering cells with Python
- Analyzing an optical pooled CRISPR screen
- Measuring a 3′ treatment response