CellProfiler

CellProfiler
Name	CellProfiler
Developer	Broad Institute (initial), Open-source community
Released	2005
Programming language	Python
Operating system	Windows, macOS, Linux
License	Open-source (BSD-like)

CellProfiler CellProfiler is an open-source image analysis software designed for quantitative measurement of biological images. It provides a modular pipeline framework for automated processing of microscopy data, enabling high-throughput assays, single-cell phenotyping, and image-based screening across diverse platforms. Originally developed to accelerate research at biomedical centers, it has since been adopted by laboratories, consortia, and industry partners working on cell biology, pharmacology, and systems biology.

Overview

CellProfiler functions as a pipeline-driven environment for image processing and feature extraction, supporting workflows from image ingestion to per-object measurement and export. It integrates with tools and institutions such as the Broad Institute, Harvard University, Massachusetts Institute of Technology, European Molecular Biology Laboratory, Stanford University, University of Cambridge, Max Planck Society, Cold Spring Harbor Laboratory, Dana-Farber Cancer Institute, Salk Institute, University of Oxford, Johns Hopkins University, University of California, San Francisco, University of California, Berkeley, Imperial College London, ETH Zurich, Wellcome Trust, National Institutes of Health, National Cancer Institute, Howard Hughes Medical Institute, Los Alamos National Laboratory, Lawrence Berkeley National Laboratory, Argonne National Laboratory, Microsoft Research, Google Research, IBM Research, Amazon Web Services, Intel Corporation, NVIDIA, Pfizer, Novartis, Roche, Merck & Co., GlaxoSmithKline, AstraZeneca, Bayer AG, Takeda Pharmaceutical Company, Genentech, Amgen, Illumina, Thermo Fisher Scientific, GE Healthcare, PerkinElmer, Siemens Healthineers, Bio-Rad Laboratories, Agilent Technologies, Bruker Corporation, CERN, European Space Agency, SpaceX, NASA, Bill & Melinda Gates Foundation, Wellcome Trust Sanger Institute, Human Genome Project, ENCODE Project, Cancer Genome Atlas, Allen Institute for Brain Science, Howard Hughes Medical Institute Janelia Research Campus, Sanger Institute, Cold Spring Harbor Laboratory Meetings.

History and development

Development began in the early 2000s with principal contributions from researchers affiliated with the Broad Institute and collaborators from Harvard University and MIT. Early releases targeted cell segmentation and feature measurement needs evident in projects like the Human Genome Project and ENCODE Project, and in large-scale screening efforts exemplified by the Cancer Genome Atlas. Over successive versions the project incorporated lessons from initiatives at Sanger Institute, Allen Institute for Brain Science, and academic centers such as Stanford University and Johns Hopkins University. Funding and infrastructure support have come from agencies and organizations including the National Institutes of Health, National Science Foundation, Wellcome Trust, and philanthropic entities like the Bill & Melinda Gates Foundation.

Key collaborators and contributors have included software engineers and scientists connected to institutions such as EMBL-EBI, Max Planck Society, Salk Institute, Dana-Farber Cancer Institute, and companies like Microsoft Research, Google Research, NVIDIA, and Intel Corporation. The project evolved alongside related bioimageinformatics tools and standards emerging from conferences and communities like ISMB, EMBO, Gordon Research Conferences, SPIE, ASCB, RSNA, and workshops at Cold Spring Harbor Laboratory.

Features and functionality

CellProfiler provides modules for image preprocessing, object identification, object measurement, and data export, supporting fluorescence, brightfield, phase-contrast, and high-content screening images. It implements algorithms influenced by work from groups at MIT, Harvard University, Stanford University, ETH Zurich, University of Oxford, and Imperial College London. Core capabilities include segmentation, deconvolution, illumination correction, texture analysis, and morphological measurement interoperable with statistical and machine learning platforms such as R (programming language), Python (programming language), scikit-image, OpenCV, TensorFlow, PyTorch, and CellProfiler Analyst.

Modules address common analysis tasks encountered in projects supported by institutions like Wellcome Trust Sanger Institute, National Institutes of Health, Broad Institute, European Molecular Biology Laboratory, and companies like Thermo Fisher Scientific and PerkinElmer. Export formats facilitate downstream analysis in systems associated with Bioconductor, Galaxy (platform), Kubernetes, Docker, Singularity, and cloud providers such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure.

Architecture and implementation

The software is implemented primarily in Python (programming language) and leverages libraries and ecosystems including NumPy, SciPy, Pandas (software), scikit-image, matplotlib, and HDF5. Its modular pipeline design parallels architectures used at institutions such as Broad Institute and projects like Bioconductor. For visualization, integration with tools and standards such as Open Microscopy Environment and formats associated with OME-TIFF has been emphasized in collaborations with EMBL-EBI and Wellcome Trust Sanger Institute.

Performance optimizations make use of compute resources and hardware from vendors and projects including NVIDIA, Intel Corporation, AMD (company), OpenCL, and implementations suitable for deployment on clusters managed with SLURM, PBS (software), or container orchestration platforms like Kubernetes and cloud infrastructures such as Amazon Web Services and Google Cloud Platform.

Applications and use cases

CellProfiler is applied to high-content screening in pharmaceutical research at companies like Pfizer, Novartis, Roche, Merck & Co., GlaxoSmithKline, and AstraZeneca, to single-cell phenotyping in academic settings such as Stanford University, Harvard University, Johns Hopkins University, and University of California, San Francisco, and to large-scale imaging consortia like the Allen Institute for Brain Science and projects linked to the Human Cell Atlas. It supports translational oncology efforts connected to Dana-Farber Cancer Institute and National Cancer Institute, developmental biology studies at Cold Spring Harbor Laboratory and Salk Institute, and neuroscience imaging workflows used at Max Planck Society institutes and Wellcome Trust Sanger Institute programs.

Use cases include drug-response assays, RNAi and CRISPR screens tied to initiatives at Broad Institute and Wellcome Trust, organoid imaging projects associated with Wellcome Trust Sanger Institute and EMBL-EBI, and pathology image analysis complementing efforts at RSNA-affiliated sites, Massachusetts General Hospital, and Mayo Clinic.

Community, licensing, and distribution

CellProfiler is distributed under an open-source license with community governance that mirrors models used by projects at Apache Software Foundation, Linux Foundation, and scientific commons supported by National Institutes of Health programs. Community contributions come from labs and companies including Broad Institute, Harvard University, Stanford University, MIT, Sanger Institute, EMBL-EBI, NVIDIA, Intel Corporation, and many academic groups. Distribution channels and reproducible deployment patterns leverage Docker, Conda, PyPI, and package repositories used by organizations like Anaconda, Inc. and GitHub. Training, workshops, and community meetings occur alongside conferences such as ASCB, EMBO, Gordon Research Conferences, and SPIE, while collaborative datasets and challenges connect to consortia like the Human Cell Atlas and Data Science Bowl.

Category:Bioimage analysis software