CellProfiler Analyst (CPA) allows interactive exploration and analysis of data, particularly from high-throughput, image-based experiments. Included is a supervised machine learning system which can be trained to recognize complicated and subtle phenotypes, for automatic scoring of millions of cells. CPA provides tools for exploring and analyzing multidimensional data, particularly data from high-throughput, image-based experiments analyzed by its companion image analysis software, CellProfiler.
Please contact us to discuss contributing to CPA, or notify us of papers referencing CPA so that we can provide the link to the paper and its results.
The CellProfiler project is based at the Broad Institute Imaging Platform. It was started by Anne E. Carpenter and Thouis (Ray) Jones in the laboratories of David M. Sabatini and Polina Golland at the Whitehead Institute for Biomedical Research and MIT’s CSAIL.
CellProfiler Analyst is distributed under the BSD License.
CPA is described in the following publications:
CellProfiler Analyst: interactive data exploration, analysis, and classification of large biological image sets by David Dao, Adam N. Fraser, Jane Hung, Vebjorn Ljosa, Shantanu Singh and Anne E. Carpenter, Bioinformatics, DOI: 10.1093/bioinformatics/btw390
CellProfiler Analyst: data exploration and analysis software for complex image-based screens by Thouis R Jones, In Han Kang, Douglas B Wheeler, Robert A Lindquist, Adam Papallo, David M Sabatini, Polina Golland and Anne E Carpenter, BMC Bioinformatics 20089:482, DOI: 10.1186/1471-2105-9-482