Datasets corresponding to publication: Label-free imaging flow cytometry: analysis and sorting of enzymatically dissociated tissues

Datasets corresponding to publication: Label-free imaging flow cytometry: analysis and sorting of enzymatically dissociated tissues.

This repository contains data to reproduce each figure contained in the manuscript
"Label-free imaging flow cytometry: analysis and sorting of enzymatically dissociated tissues".
The folders:
- 20151028_TiagoF_MaikH_Ader_Retina_Nrl-GFP-P10
- 20190114_Maik_Ahsan_retina_sorting
- 20190204_MaikH_Retina_Nrl_P04
- 20190624_Maik_Ahsan_Neutrophils_AI_Sorting
- 20191021_MaikH_Nrl_P05
- 20210304_MaikH_Retina_mGluR6-GFP_P04
- 20210305_MaikH_Nrl_P04_Sorting
- DataSet_Cones_Gated
- DataSet_Cones_Raw
- DataSet_HRO_Labelled
- DataSet_Nrl-eGFP_Gated
- DataSet_Nrl-eGFP_Raw
contain data (either original, or readily gated/labelled)

The folders:
- Figure 2...Figure S8
contain Python scripts and further resources to reproduce plots and analyses.
There are folders for each subpanel in each figure and a "HowTo.txt" in each directory describes
how to proceed.  
To provide a Python environment that contains all the required Python packages of the correct version,
we designed PyBox 0.1.0. PyBox is essentially a readily installed Python environment in a zip file.
Alternatively, the Python environment can manually be installed as described here:
https://github.com/maikherbig/PyBox#which-packages-are-contained-in-pybox