Cluster analysis of two colour SMLM data and analysis of the distances between nearest neighbouring clusters

Python code that reads GDSCSMLM FitResults csv files from two different colour channels and runs DBSCAN cluster analysis on the data. The distance between each mCherry cluster and the nearest mNeonGreen cluster in the same image was determined by calculating the Euclidian distance to all the mNeonGreen clusters in the cell and recording the shortest distance. The distances between different coloured clusters identified for each file and for all the files in a folder are displayed in histograms. This code was written as part of ongoing research of the LIVE-PAINT super-resolution imaging technique in the Regan and Horrocks Labs at the University of Edinburgh.

Zoe Gidden. (2023). Cluster analysis of two colour SMLM data and analysis of the distances between nearest neighbouring clusters. Zenodo. https://doi.org/10.5281/zenodo.8060654