wayscience / cell-health-data

Data processing for the Cell Painting data from the Cell Health experiments

Cell Health Data Processing

Overview

This is a data repository storing instructions on how to:

0. Download the Cell Health Cell Painting dataset (IDR0080)
1. Perform single nuclei segmentation
2. Extract single cell embeddings
   • Using CellProfiler
   • Using DeepProfiler
3. Preprocess both kinds of embeddings using pycytominer
4. Classify single-cell phenotypes using models from the phenotypic_profiling_model repository.

These data were originally used as part of the publication Way et al. 2021.

Predicting cell health phenotypes using image-based morphology profiling Gregory P. Way, Maria Kost-Alimova, Tsukasa Shibue, William F. Harrington, Stanley Gill, Federica Piccioni, Tim Becker, Hamdah Shafqat-Abbasi, William C. Hahn, Anne E. Carpenter, Francisca Vazquez, and Shantanu Singh Molecular Biology of the Cell 2021 32:9, 995-1005

Note: Not all data are stored in this repository. Some data are too large.

Reproducibility

Specific code and steps used are available within each module folder.

The Way Lab always strives for readable, reproducible computational biology analyses and workflows. If you struggle to understand or reproduce anything in this repository please file an issue!