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CellProfiler: image analysis software for identifying and quantifying cell phenotypes

Genome biology · 2006 · Vol. 7(10) · pp. R100–R100

Anne E. Carpenter(Whitehead Institute for Biomedical Research)Thouis R. Jones(Massachusetts Institute of Technology)Michael R. Lamprecht(Whitehead Institute for Biomedical Research)Colin Clarke(Whitehead Institute for Biomedical Research)In Han Kang(Massachusetts Institute of Technology)Ola Friman(Brigham and Women's Hospital)David A. Guertin(Whitehead Institute for Biomedical Research)Joseph Chang(Whitehead Institute for Biomedical Research)Robert A. Lindquist(Whitehead Institute for Biomedical Research)Jason Moffat(Whitehead Institute for Biomedical Research)Polina Golland(Massachusetts Institute of Technology)David M. Sabatini✉(Massachusetts Institute of Technology)

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Abstract

Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).

Cell Image Analysis Techniques Genetics, Bioinformatics, and Biomedical Research Image Processing Techniques and ApplicationsBiologyHuman geneticsComputational biologyPhenotypeEvolutionary biologyGenome BiologySoftwareGeneticsBioinformaticsGenomics

MeSH terms

Dose-Response Relationship, DrugImage Processing, Computer-AssistedModels, GeneticMutationPhenotypeSoftwareReproducibility of ResultsGene Expression Profiling