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