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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.
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Core tools are maintained under the [cytomining GitHub organization](https://github.com/cytomining) by [contributors](https://github.com/orgs/cytomining/people) from the [Way Lab](https://www.waysciencelab.com/) at the University of Colorado Anschutz Medical Campus and beyond.
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Core tools are maintained under the [Cytomining GitHub organization](https://github.com/cytomining) by [contributors](https://github.com/orgs/cytomining/people) from the [Way Lab](https://www.waysciencelab.com/) at the University of Colorado Anschutz Medical Campus and beyond.
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Experimental and emerging tools are developed under the [WayScience GitHub organization](https://github.com/WayScience) before graduating into the core ecosystem.
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## Impact
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Cytomining tools have been adopted across academia and industry for large-scale drug discovery and functional genomics.
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`Pycytominer` underpins some of the largest publicly available image-based profiling datasets, including the [JUMP Cell Painting dataset](https://jump-cellpainting.broadinstitute.org/) (over 136,000 chemical and genetic perturbations profiled across 12 partner sites) the [LINCS Drug Repurposing](https://github.com/broadinstitute/lincs-cell-painting) Cell Painting dataset, and the [EU-OPENSCREEN](https://www.eu-openscreen.eu/) Bioactive Compound Set profiled across multiple imaging sites.
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[`Pycytominer`](/tools/pycytominer/) underpins some of the largest publicly available image-based profiling datasets, including the [JUMP Cell Painting dataset](https://jump-cellpainting.broadinstitute.org/) (over 136,000 chemical and genetic perturbations profiled across 12 partner sites) the [LINCS Drug Repurposing](https://github.com/broadinstitute/lincs-cell-painting) Cell Painting dataset, and the [EU-OPENSCREEN](https://www.eu-openscreen.eu/) Bioactive Compound Set profiled across multiple imaging sites.
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It has also processed many of the 31+ datasets in the [Cell Painting Gallery](https://broadinstitute.github.io/cellpainting-gallery/).
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The foundational [Caicedo et al. 2017](https://doi.org/10.1038/nmeth.4397) review has accumulated over 670 citations, and individual tool papers have together been cited more than 150 times since 2024.
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Packages are downloaded thousands of times per month via [PyPI] download statistics (https://pypistats.org/).
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## History
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The ecosystem traces its roots to the [Imaging Platform](https://www.broadinstitute.org/imaging) 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.
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The ecosystem traces its roots to the [Imaging Platform](https://www.broadinstitute.org/imaging) at the Broad Institute, where early contributors including Anne Carpenter, Shantanu Singh, Allen Goodman, and others developed [`cytominer`](https://github.com/cytomining/cytominer), an R package for processing high-content imaging data.
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In 2016, members of this community co-founded the [CytoData Society](https://www.cytodata.org/) to unite researchers across academia and industry around image-based profiling.
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The following year, the team contributed the landmark [Caicedo et al. 2017](https://doi.org/10.1038/nmeth.4397) review in _Nature Methods_ that established the field's foundational analysis standards.
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Since 2021, the [Way Lab](https://www.waysciencelab.com/) has driven a major expansion of the ecosystem — migrating from R to Python with `Pycytominer` and building a modern infrastructure stack including `CytoTable` and `coSMicQC`.
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Since 2021, the [Way Lab](https://www.waysciencelab.com/) has driven a major expansion of the ecosystem — migrating from R to Python with [`Pycytominer`](/tools/pycytominer/) and building a modern infrastructure stack including [`CytoTable`](/tools/cytotable/), [`coSMicQC`](/tools/cosmicqc/), and others.
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In 2026, members of the CytoData community published an updated review, [Serrano et al.](https://doi.org/10.1038/s44320-026-00197-7) in _Molecular Systems Biology_, surveying progress and new challenges in image-based profiling.
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Today, Cytomining tools are used by research groups worldwide for drug discovery, functional genomics, and cell biology.
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## Community
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## Communities
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We are proud members of the [CytoData](https://www.cytodata.org/)community, which hosts an annual symposium bringing together researchers and developers working on image-based profiling.
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We are proud members of the [CytoData Society](https://www.cytodata.org/)and [The Society of Biomolecular Imaging and Informatics](https://sbi2.org/), which hosts an annual symposium bringing together researchers and developers working on image-based profiling.
`buscar` scores perturbations directly on single-cell distributions using Earth Mover's Distance, preserving heterogeneity throughout hit calling.
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**Problem:** Population-level hit calling averages away biologically meaningful cell-to-cell variation, making heterogeneous responses and rare subpopulations invisible to standard metrics.
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- Score perturbation efficacy via Earth Mover's Distance
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- Assess specificity with off-target scoring to reduce false positives
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- Preserve single-cell heterogeneity throughout hit calling
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- Integrates directly with `Pycytominer`, `coSMicQC`, and `CytoTable` workflows
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- Integrates directly with [`Pycytominer`](/tools/pycytominer/), [`coSMicQC`](/tools/cosmicqc/), and [`CytoTable`](/tools/cytotable/) workflows
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**[View on GitHub →](https://github.com/WayScience/buscar)**
`iceberg-bioimage` scans any image store into a versioned Apache Iceberg catalog that directly exports Cytomining-compatible Parquet warehouses.
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**Problem:** Raw bioimaging archives have no standard catalog — finding, versioning, and joining images to downstream data requires bespoke scripts per lab.
`OME-arrow` embeds images as first-class columns in Apache Arrow tables, so features, metadata, and pixel data travel together and can be queried or exported as tensors.
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**Problem:** Images and feature tables live in separate systems — linking a numeric outlier back to its source cell requires error-prone manual joins across formats.
`ZEDprofiler` extracts morphological features directly from 3D volumetric images, including anisotropic voxel spacing correction — no GPU required.
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**Problem:** Classical profiling tools extract only 2D features, leaving organoid, cleared-tissue, and z-stack experiments without a CPU-efficient extractor.
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#### Peer-reviewed
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-**CytoTable ([tool page](https://cytomining.github.io/tools/cytotable/)):** Bunten, D. et al. Scalable data harmonization for single-cell image-based profiling with CytoTable.
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-**CytoTable ([tool page](https://cytomining.github.io/tools/cytotable/) · [GitHub](https://github.com/cytomining/CytoTable)):** Bunten, D. et al. Scalable data harmonization for single-cell image-based profiling with CytoTable.
-**Pycytominer ([tool page](https://cytomining.github.io/tools/pycytominer/)):** Serrano, E. et al. Reproducible image-based profiling with Pycytominer.
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-**Pycytominer ([tool page](https://cytomining.github.io/tools/pycytominer/) · [GitHub](https://github.com/cytomining/pycytominer)):** Serrano, E. et al. Reproducible image-based profiling with Pycytominer.
-**copairs ([tool page](https://cytomining.github.io/tools/copairs/)):** Kalinin, A.A. et al. A versatile information retrieval framework for evaluating profile strength and similarity.
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-**copairs ([tool page](https://cytomining.github.io/tools/copairs/) · [GitHub](https://github.com/cytomining/copairs)):** Kalinin, A.A. et al. A versatile information retrieval framework for evaluating profile strength and similarity.
-**DeepProfiler ([tool page](https://cytomining.github.io/tools/deepprofiler/)):** Moshkov, N. et al. Learning representations for image-based profiling of perturbations.
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-**DeepProfiler ([tool page](https://cytomining.github.io/tools/deepprofiler/) · [GitHub](https://github.com/cytomining/DeepProfiler)):** Moshkov, N. et al. Learning representations for image-based profiling of perturbations.
-**buscar ([tool page](https://cytomining.github.io/experimental/buscar/)):** Serrano, E., Li, W.S. & Way, G.P. Single-cell hit calling in high-content imaging screens with Buscar.
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-**buscar ([tool page](https://cytomining.github.io/experimental/buscar/) · [GitHub](https://github.com/WayScience/buscar)):** Serrano, E., Li, W.S. & Way, G.P. Single-cell hit calling in high-content imaging screens with Buscar.
-**coSMicQC ([tool page](https://cytomining.github.io/tools/cosmicqc/)):** Tomkinson, J. et al. Stellar quality control for single-cell image-based profiling with coSMicQC.
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-**coSMicQC ([tool page](https://cytomining.github.io/tools/cosmicqc/) · [GitHub](https://github.com/cytomining/coSMicQC)):** Tomkinson, J. et al. Stellar quality control for single-cell image-based profiling with coSMicQC.
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## Governance
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Cytomining uses a lightweight governance model centered on maintainers and public decision-making.
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We keep policy concise and bias toward transparent, repository-native workflows over heavy process.
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We keep policy concise and transparent.
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-**Stewardship:** Repositories are maintained by designated maintainers in the `Cytomining` organization.
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-**Stewardship:** Repositories are maintained by designated maintainers in the [`Cytomining`](https://github.com/cytomining) organization.
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-**Decision-making:** Day-to-day technical decisions happen in public issues, pull requests, and our public [Discord](https://discord.gg/dgEDz6xzfJ).
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-**Consensus first:** Maintainers seek rough consensus from active contributors before merging impactful changes.
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-**Escalation path:** When consensus is unclear, maintainers make a final call, document rationale, and revisit with new evidence.
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This reflects how the organization operates today and is intentionally compact so contributors can understand how decisions get made without navigating a large policy surface.
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### Organizational structure
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The Cytomining ecosystem currently spans two GitHub organizations with distinct roles.
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The [**cytomining**](https://github.com/cytomining) organization hosts production-ready tools that have reached stable APIs, published documentation, test coverage, and community adoption.
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Tools here are maintained collaboratively by contributors from the [Way Lab](https://www.waysciencelab.com/) at the University of Colorado Anschutz and the broader image-based profiling community.
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The [**WayScience**](https://github.com/WayScience) organization serves as an incubator for next-generation tools under active development.
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It is the primary home for roadmap work: tools here are experimental, may have unstable APIs, and have not yet graduated into [`Cytomining`](https://github.com/cytomining).
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The two organizations are complementary.
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[`WayScience`](https://github.com/WayScience) is where new ideas are prototyped and validated; [`Cytomining`](https://github.com/cytomining) is where they become community infrastructure.
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Core production tools ([`Pycytominer`](/tools/pycytominer/), [`CytoTable`](/tools/cytotable/), [`coSMicQC`](/tools/cosmicqc/), [`copairs`](/tools/copairs/), [`DeepProfiler`](/tools/deepprofiler/), [`CytoDataFrame`](/tools/cytodataframe/)) live in [`Cytomining`](https://github.com/cytomining).
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Roadmap tools ([`buscar`](/experimental/buscar/), [`OME-arrow`](/experimental/ome-arrow/), [`iceberg-bioimage`](/experimental/iceberg-bioimage/), [`ZEDprofiler`](/experimental/zedprofiler/)) live in [`WayScience`](https://github.com/WayScience) until they are ready to graduate.
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### Graduation process
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A tool is considered ready to migrate from [`WayScience`](https://github.com/WayScience) (or any other repository from other organizations) into [`Cytomining`](https://github.com/cytomining) when it meets the following criteria:
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-**Within scope** — the tool must be purpose-built for scientists who perform image-based profiling.
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-**Stable API** — no breaking changes anticipated in the near term; a versioned release has been tagged
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-**Documentation** — a published documentation site covering installation, usage, and API reference
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-**Test coverage** — a CI-passing test suite with meaningful coverage (>80%) of core functionality
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-**Publication or preprint** — a citable reference describing the tool's design and validation
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## Code of Conduct
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Participation in Cytomining spaces is expected to follow the organization-wide Code of Conduct:
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