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@WayScience

The Way Lab

The Way Lab at CU Anschutz

Welcome to the open-source GitHub organization hosted by The Way Lab.

We are a team of scientists and engineers developing methods and software for analyzing microscopy images of cells. Our mission is to reduce human suffering.

Our website contains complete details of our research projects, team members, and funding: https://www.waysciencelab.com/

Check out a few of our open-source projects!

Select Publications

Tomkinson, J., Kern, R., Mattson, C. et al. Toward generalizable phenotype prediction from single-cell morphology representations. BMC Methods 1, 17 (2024). doi: https://doi.org/10.1186/s44330-024-00014-3; GitHub Repository: https://github.com/WayScience/phenotypic_profiling/

Lippincott, M.J., Tomkinson, J., Bunten, D. et al. A morphology and secretome map of pyroptosis. Molecular Biology of the Cell doi: https://doi.org/10.1101/2024.04.26.591386; GitHub Repository: https://github.com/WayScience/pyroptosis_signature_data_analysis

Serrano, E., Chandrasekaran, S.N., Bunten, D. et al. Reproducible image-based profiling with Pycytominer. Nature Methods (2025). doi: https://doi.org/10.1038/s41592-025-02611-8; GitHub Repository: https://github.com/cytomining/pycytominer

Tomkinson, J., Mattson, C., Mattson-Hoss, M. et al. High-content microscopy and machine learning characterize a cell morphology signature of NF1 genotype in Schwann cells. BioRxiv (2025). doi: https://doi.org/10.1101/2024.09.11.612546

Select Software

Select Projects

We are leading multidisciplinary scientists in a variety of team-science initiatives.

Pediatric Cancer Cell Morphology Atlas

We are developing a reference Cell Painting data set of pediatric cancer cell lines, and performing several high-throughput, high-content phenotypic drug screens.

3D profiling of Neurofibromatosis Type 1 patient-derived organoids

We are developing a 3D image analysis pipeline to profile patient-derived organoids from neurofibromatosis type 1 (NF1) patients, and we will be performing several high-throughput, high-content phenotypic drug screens.

Finding new therapeutics for cardiac fibrosis

We are identifying fundamental differences between cardiac fibroblasts from patients with and without heart failure, and we are developing a high-throughput, high-content phenotypic drug screen to identify new therapeutics for cardiac fibrosis.

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  1. ome-arrow ome-arrow Public

    Using OME specifications with Apache Arrow for fast, queryable, and language agnostic bioimage data.

    Python 6 1

  2. buscar buscar Public

    Single cell hit calling for high-content screens

    Python 6 2

  3. pediatric_cancer_atlas_profiling pediatric_cancer_atlas_profiling Public

    Image analysis and image-based profiling of pediatic cancer cell lines to extract morphological profiles.

    Jupyter Notebook 6 5

  4. nf1_schwann_cell_painting_data nf1_schwann_cell_painting_data Public

    This repository contains all the modules to perform image-based analysis with CellProfiler on NF1 Schwann cell data.

    Jupyter Notebook 6 6

  5. CPBS7601 CPBS7601 Public

    Course on computing skills in biomedical informatics

    Jupyter Notebook 5 21

  6. NF1_3D_organoid_profiling_pipeline NF1_3D_organoid_profiling_pipeline Public

    Jupyter Notebook 4 3

Repositories

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