About

Cytomining is an open-source software ecosystem for single-cell image-based profiling — the practice of measuring thousands of cell morphology features from microscopy images to understand how cells respond to genetic, chemical, or environmental perturbations.

Core tools are maintained under the Cytomining GitHub organization by contributors from the Way Lab at the University of Colorado Anschutz Medical Campus and beyond. Experimental and emerging tools are developed under the WayScience GitHub organization before graduating into the core ecosystem.

Impact #

Cytomining tools have been adopted across academia and industry for large-scale drug discovery and functional genomics. Pycytominer underpins some of the largest publicly available image-based profiling datasets, including the JUMP Cell Painting dataset (over 136,000 chemical and genetic perturbations profiled across 12 partner sites) the LINCS Drug Repurposing Cell Painting dataset, and the EU-OPENSCREEN Bioactive Compound Set profiled across multiple imaging sites. It has also processed many of the 31+ datasets in the Cell Painting Gallery.

The foundational Caicedo et al. 2017 review has accumulated over 670 citations, and individual tool papers have together been cited more than 150 times since 2024. Packages are downloaded thousands of times per month via [PyPI] download statistics (https://pypistats.org/).

History #

The ecosystem traces its roots to the Imaging Platform at the Broad Institute, where early contributors including Anne Carpenter, Shantanu Singh, Allen Goodman, and others developed cytominer, an R package for processing high-content imaging data.

In 2016, members of this community co-founded the CytoData Society to unite researchers across academia and industry around image-based profiling. The following year, the team contributed the landmark Caicedo et al. 2017 review in Nature Methods that established the field’s foundational analysis standards.

Since 2021, the Way Lab has driven a major expansion of the ecosystem — migrating from R to Python with Pycytominer and building a modern infrastructure stack including CytoTable, coSMicQC, and others. In 2026, members of the CytoData community published an updated review, Serrano et al. in Molecular Systems Biology, surveying progress and new challenges in image-based profiling. Today, Cytomining tools are used by research groups worldwide for drug discovery, functional genomics, and cell biology.

Communities #

We are proud members of the CytoData Society and The Society of Biomolecular Imaging and Informatics, which hosts an annual symposium bringing together researchers and developers working on image-based profiling.