• Author: Jeffrey M. Hokanson jeffrey@hokanson.us

FlowML provides a python tool chain for the all the common steps in analyzing flow cytometry data with matplotlib based visualizations. Coupled with an IPython Notebook, FlowML allows easy, interactive, programmatic data analysis.

Clone the repository, then run the start_server.sh script on a Mac or Linux system.

There are many questions we want to ask of Flow Cytometry data -- some we don't even know yet. The problem is that GUI interfaces have a relatively limited ability to interact with data and programming tools are often outside of the skill set of most technicians.

• Commerical GUI

• FlowJo
• Kaluza
• GemStone

• Free or Open Source GUI

• Flowing Software

• Research

• SPADE by Diana Pe'er's lab (Matlab based)
• CYT by Peng Qiu (Matlab based)

• Software toolchains

• FCM Python
• flowCore Biocnductor toolkit (R-language)

• Other

• FCS A Node.js package for reading FCS files

The code is under heavy development and the following features are planned on being added.

• Reading and writing FCS files
• 1D and 2D histograms and kernel density estimator plots
• Gating (drawing polygons to select data) inside the IPython Notebook
• Automated gating algorithms inside other packages, namely the Bioconductor's package flowCore and its descendants
• Advanced dimension reduction techniques
  • t-SNE and viSNE
  • SPADE
  • Others available in Scikit-learn.

This project uses some code developed by Jacob Frelinger for FCM for writing FCS files.