This repository contains the code to analyze live cell timelapse microscopy data of apoptosis in HeLa cells. The goal of this analysis repository is to build a pipeline and framework to analyze live cell timelapse microscopy data modes. Specifically, multi-channel fluorescence microscopy data. We will do use by extracting morphology features from images using CellProfiler and using the coordinate information to extract single cell representation using a self supervised learning approach. The self supervised learning approach is implemented by using scDINO.
The sample data and upstream analysis of such data, including image analysis with CellProfiler and image-profiling with CytoTable and pycytominer, can be found in the sibling repository live_cell_timelapse_apoptosis.
For each of the modules there are specific conda environments that are used to run the code. The conda environments can be found in the environments directory. For instructions on how to create the conda environments, please refer to the README in the environments(environments) directory.