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<br> "Label-free imaging flow cytometry: analysis and sorting of enzymatically dissociated tissues".<br> The folders:<br> - 20151028_TiagoF_MaikH_Ader_Retina_Nrl-GFP-P10<br> - 20190114_Maik_Ahsan_retina_sorting<br> - 20190204_MaikH_Retina_Nrl_P04<br> - 20190624_Maik_Ahsan_Neutrophils_AI_Sorting<br> - 20191021_MaikH_Nrl_P05<br> - 20210304_MaikH_Retina_mGluR6-GFP_P04<br> - 20210305_MaikH_Nrl_P04_Sorting<br> - DataSet_Cones_Gated<br> - DataSet_Cones_Raw<br> - DataSet_HRO_Labelled<br> - DataSet_Nrl-eGFP_Gated<br> - DataSet_Nrl-eGFP_Raw<br> contain data (either original, or readily gated/labelled)<br> <br> The folders:<br> - Figure 2...Figure S8<br> contain Python scripts and further resources to reproduce plots and analyses.<br> There are folders for each subpanel in each figure and a "HowTo.txt" in each directory describes<br> how to proceed. <br> To provide a Python environment that contains all the required Python packages of the correct version,<br> we designed PyBox 0.1.0. PyBox is essentially a readily installed Python environment in a zip file.<br> Alternatively, the Python environment can manually be installed as described here:<br> https://github.com/maikherbig/PyBox#which-packages-are-contained-in-pybox