PyCytoData: An Elegant Data Analysis Tool for CyTOF

Do you ever dream of using a single pipeline for all your CyTOF needs? Look no further: PyCytoData is all you need! We offer a complete pipeline for you to both acquire data as well as do downstream analyses. This is a flexible and extensible to support future packages and other workflows.

To get started, you can reference this quick example:

>>> from PyCytoData import DataLoader
>>> exprs = DataLoader.load_dataset(dataset = "levine13")
Would you like to download levine13? [y/n]y

Download in progress...
This may take quite a while, go grab a coffee or cytomulate it!
>>> exprs.preprocess(arcsinh=True)
Runinng Arcsinh transformation...
>>>  exprs.run_dr_methods(methods = ["PCA", "UMAP", "ICA"])
Running PCA
Running ICA
Running UMAP

For more detailed documentations and examples, look at the topics and tutorials below! Enjoy your journey working with CyTOF datasets!

Getting Started

• Installation Guide
• Quickstart Guide

Tutorial

• The PyCytoData Object
• File IO and Datasets
• CyTOF Data Preprocessing
• Dimension Reuction with CytofDR

Development

• Integration with PyCytoData
• Contribution Guideline
• Building and Testing
• Development and Roadmap
• Changelog
• License

Full API Reference

• API Reference

Resources

• References
• Dr. Xinlei (Shery) Wang
• Dr. Tao Wang
• DBAI
• GitHub

Resources

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

• GitHub Page for project development