Python package for image-based profiling
An in-memory data analysis format for single-cell profiles alongside their corresponding images and segmentation masks.
Single cell Morphology Quality Control (coSMicQC)
Software to classify biological phenotypes from single-cell image-based morphology profiles
Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic
Exploratory data analysis for image-based morphological profiling
Implementation of DEEP-MAP (see reference)
Tutorials and helpers for downstream analysis of Cell Painting data with scverse tools (anndata, scanpy, decoupler, pertpy, squidpy, rapids-singlecell)
Batch integration for morphological profiling using variational inference
Predict a compound's mechanism of action from cell images. End-to-end reproducible pipeline on open Cell Painting data: 5-channel microscopy → segmentation → morphological fingerprints → MoA retrieval.
Validate the semantic correctness, metadata completeness, provenance and AI readiness of Cell Painting datasets represented in AnnData.
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