Cytomulate: Accurate and Efficient Simulation of CyTOF data

Cytomulate is a package to simulation realistic data for Mass Cytometry or Cytometry by Time-of-Flight (CyTOF). We support both model-based through Creation Mode and real-data-based simulation through Emulation Mode. Cytomulate serves as solutions to benchmarking, method validation, prototyping, and more. You can easily generate realistic and accurately CyTOF simulations within seconds.

Using our unified framework compatible with PyCytoData, you can stay within our ecosystem: starting from simulation to precessing, you can then select the best dimension reduction method for your dataset and proceed onto other downstream analyses. All you need is a few simple commands! For more details, read our tutorials and documentations linked below! Or try this example:

>>> from cytomulate import CreationCytofData

>>> cytof_data = CreationCytofData()
>>> cytof_data.initialize_cell_types()
>>> expression_matrices, labels, _, _ = cytof_data.sample(n_samples = 100)

When in doubt, Cytomulate it!

Getting Started

• Installation Guide
• Quickstart Guide

Tutorial

• Emulation Mode
• Creation Mode
• Cytomulate CLI
• Complex Simulations
• Model and Data Visualization
• Should I install PyCytoData?
• Benchmark Analyses

Development

• Contribution Guideline
• Building and Testing
• Development and Roadmap
• Changelog
• License

Full API Reference

• API Reference

Resources

For our paper, read our preprint here.

For more resources on our labs, collaborators, and related projects, please visit the following:

• Dr. Xinlei (Shery) Wang faculty page

• Dr. Tao Wang Lab

• Database for Actionable Immunology (DBAI) for more computational immunology-related tools

For project development and newest updates, consider visiting the following:

• Our Github