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

Jupyter Notebook 88.58% Python 11.42%

cell-health-data's Introduction

Cell Health Data Processing

This is a data repository storing instructions on how to:

  1. Download the Cell Health Cell Painting dataset (IDR0080)
  2. Perform segmentation
  3. Define a new single-cell focused dataset of isolated single cells
  4. Compute single cell embeddings
    • Using CellProfiler
    • Using DeepProfiler
  5. Process both kinds of embeddings using pycytominer

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.

Step 1 - IDR Download

See 0.image-download for more details.

# Make sure to follow all steps in `0.data-download/README.md` first
# This includes one step to test and confirm download configuration
cd 0.image-download
bash download_images.sh

Step 2 - Segmentation

cell-health-data's People

Contributors

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