This is a README for the imaging flow cytometry protocol

For more information, see
H. Hennig, P. Rees, T. Blasi, L. Kamentsky, J. Hung, D. Dao, A.E. Carpenter, and A. Filby. An open-source solution for advanced imaging flow cytometry data analysis using machine learning. Methods, in press (2016)

Step 1: Use python app (or Matlab script) to read cif file and generate image tiles.
input: example.cif
output: Step1_Matlab_tiling.zip
Note: This cif file serves as a quick example, it contains only a very small number of images.

Step 2: Segment cells and extract featurs with Cellprofiler 
input: Step2_input_tiled_tifs.zip
output: Step2_CP_output.zip
Note: The input images are Jurkat cells, the data set was analyzed in the article above (Hennig et al., Methods, 2016), where a label-free prediction of the cell cycle is demonstrated. The corresponding CellProfiler pipeline to extract features is provided.