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CellProfiler: image analysis software for identifying and quantifying cell phenotypes

Anne E Carpenter1, Thouis R Jones12, Michael R Lamprecht1, Colin Clarke12, In Han Kang2, Ola Friman3, David A Guertin1, Joo Han Chang1, Robert A Lindquist1, Jason Moffat1, Polina Golland2 and David M Sabatini14*

Author Affiliations

1 Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA

2 Computer Sciences and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02142, USA

3 Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA

4 Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA

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Genome Biology 2006, 7:R100 doi:10.1186/gb-2006-7-10-r100

Published: 31 October 2006

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).