CellProfiler is free open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically.
To run CellProfiler, you need to have X11 forwarding setup and an X11 emulator on your local computer. Please see the GUI Programs wiki page for information on this.
CellProfiler is primarily designed to be a GUI application. However, it does have a batch processing mode, which is how it is intended to be used at the Research Computing. To run CellProfiler in batch mode, you should include the -c or --run-headless option. Also, you want to use CELLPROFILER_USE_XVFB="1"
Here is a list of the CellProfiler command line options:
Usage: CellProfiler.py [options] [<output-file>]) where <output-file> is the optional filename for the output file of measurements when running headless
Options: -h, --help show this help message and exit -p PIPELINE_FILENAME, --pipeline=PIPELINE_FILENAME Load this pipeline file on startup -c, --run-headless Run headless (without the GUI) -r, --run Run the given pipeline on startup --worker=WORKER_MODE_URL Enter worker mode for the CellProfiler distributing work at URL (implies headless) --worker-timeout=WORKER_TIMEOUT Number of seconds the worker will continue trying to find work before exiting. -o OUTPUT_DIRECTORY, --output-directory=OUTPUT_DIRECTORY Make this directory the default output folder -i IMAGE_DIRECTORY, --image-directory=IMAGE_DIRECTORY Make this directory the default input folder -f FIRST_IMAGE_SET, --first-image-set=FIRST_IMAGE_SET The one-based index of the first image set to process -l LAST_IMAGE_SET, --last-image-set=LAST_IMAGE_SET The one-based index of the last image set to process -g GROUPS, --group=GROUPS Restrict processing to one grouping in a grouped pipeline. For instance, "-g ROW=H,COL=01", will process only the group of image sets that match the keys. --html Output HTML help for all modules. Use with the -o option to specify the output directory for the files. Assumes -b. --plugins-directory=PLUGINS_DIRECTORY CellProfiler will look for plugin modules in this directory (headless-only). --ij-plugins-directory=IJ_PLUGINS_DIRECTORY CellProfiler will look for ImageJ plugin modules in this directory (headless-only). --jvm-heap-size=JVM_HEAP_SIZE This is the amount of memory reserved for the Java Virtual Machine (similar to the java -Xmx switch).Example formats: 512000k, 512m, 1g -b, --do-not-build, --do-not_build Do not build C and Cython extensions --build-and-exit Build extensions, then exit CellProfiler --do-not-fetch Do not fetch external binary dependencies --fetch-and-overwrite Overwrite external binary depencies if hash does not match --ilastik Run Ilastik instead of CellProfiler. Ilastik is a pixel-based classifier. See www.ilastik.org for more details. -d DONE_FILE, --done-file=DONE_FILE The path to the "Done" file, written by CellProfiler shortly before exiting --measurements Open the pipeline file specified by the -p switch and print the measurements made by that pipeline --data-file=DATA_FILE Specify a data file for LoadData modules that use the "From command-line" option -L LOG_LEVEL, --log-level=LOG_LEVEL Set the verbosity for logging messages: 10 or DEBUG for debugging, 20 or INFO for informational, 30 or WARNING for warning, 40 or ERROR for error, 50 or CRITICAL for critical, 50 or FATAL for fatal. Otherwise, the argument is interpreted as the file name of a log configuration file (see http://docs.python.org/library/logging.config.html for file format)
If you publish research that uses CellProfiler you have to cite it as follows:
- Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin DA, Chang JH, Lindquist RA, Moffat J, Golland P, Sabatini DM (2006) CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology 7:R100. PMID: 17076895
- Lamprecht MR, Sabatini DM, Carpenter AE (2007) CellProfiler: free, versatile software for automated biological image analysis. Biotechniques 42(1):71-75. PMID: 17269487
- Jones TR, Carpenter AE, Lamprecht MR, Moffat J, Silver S, Grenier J, Root D, Golland P, Sabatini DM (2009) Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning. PNAS 106(6):1826-1831/doi: 10.1073/pnas.0808843106. PMID: 19188593 PMCID: PMC2634799
- Jones TR, Kang IH, Wheeler DB, Lindquist RA, Papallo A, Sabatini DM, Golland P, Carpenter AE (2008) CellProfiler Analyst: data exploration and analysis software for complex image-based screens. BMC Bioinformatics 9(1):482/doi: 10.1186/1471-2105-9-482. PMID: 19014601 PMCID: PMC2614436