Chromatin texture analysis of (induced) senescence in IMR90 cells

Workflow for STED data

1. feature_extraction_sted.ipynb to extract GLCM texture and auxiliary features from .h5 files created during automated acquisitions
1. quality_control_sted.ipynb for ML-assisted quality control (good/bad image classification) based on features
1. oldyoung_cls_sted.ipynb and feature_embedding_plots.ipynb for old/young classification of treated cells and generation of t-SNE plots / example image extraction.

1. For overview images from automated STED runs: overview_extraction_from_h5.ipynb to save individual images as TIFF
1. Stitch into large images using bigstitcher_overview_stitch_wrapper.ipynb
1. Segment individual cells using cellpose_segmentation.ipynb
1. feature_extraction_overview.ipynb to extract GLCM texture and auxiliary features for each cell from overview images and segmentation masks
1. oldyoung_cls_overview.ipynb and feature_embedding_plots.ipynb for old/young classification of treated cells and generation of t-SNE plots / example image extraction.

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
auxiliary_scripts		auxiliary_scripts
data		data
old_analysis		old_analysis
README.md		README.md
bigstitcher_overview_stitch.ijm		bigstitcher_overview_stitch.ijm
bigstitcher_overview_stitch_wrapper.ipynb		bigstitcher_overview_stitch_wrapper.ipynb
cellpose_segmentation.ipynb		cellpose_segmentation.ipynb
example_feature_plots.ipynb		example_feature_plots.ipynb
feature_embedding_plots.ipynb		feature_embedding_plots.ipynb
feature_extraction_overview.ipynb		feature_extraction_overview.ipynb
feature_extraction_sted.ipynb		feature_extraction_sted.ipynb
glcm_utils.py		glcm_utils.py
oldyoung_cls_overview.ipynb		oldyoung_cls_overview.ipynb
oldyoung_cls_sted.ipynb		oldyoung_cls_sted.ipynb
overview_extraction_from_h5.ipynb		overview_extraction_from_h5.ipynb
quality_control_sted.ipynb		quality_control_sted.ipynb