Version |
Documentation |
Forum |
|---|---|---|
 |
 |
 |
CellProfiler Analyst 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 complex and subtle phenotypes, for automatic scoring of millions of cells.
This is the developer site for CellProfiler Analyst. The regular home page for CellProfiler Analyst is here: https://cellprofileranalyst.org/
Download CellProfiler Analyst
When running from source, CellProfiler Analyst requires JDK 1.8 to be installed (not just JRE). Check the Java path.
Please note that this is the development branch of CPA and it will be updated on regular basis.
Find all releases here.
For a head start, download example dataset here: Example Dataset for CPA (zipped)
Building CPA on your machine requires CellProfiler dependencies. Check the wiki for more detailed installation instructions.
- Pandas
- Seaborn
- Scikit-learn
- Python-Javabridge
- Verlib
- Python-bioformats
https://github.com/CellProfiler/CellProfiler-Analyst/wiki
CellProfiler Analyst development is discussed on the CellProfiler Forum list.
Please attach sufficient information to reproduce the bug. For many bugs, it is appropriate to attach a properties file, a training set, or a screenshot.
David Dao, Adam N Fraser, Jane Hung, Vebjorn Ljosa, Shantanu Singh and Anne E Carpenter
CellProfiler Analyst: interactive data exploration, analysis and classification of large biological image sets
Bioinformatics (2016) doi:10.1093/bioinformatics/btw390
Thouis R Jones, In Han Kang, Douglas B Wheeler, Robert A Lindquist, Adam Papallo, David M Sabatini, Polina Golland and Anne E Carpenter
CellProfiler Analyst: data exploration and analysis software for complex image-based screens
BMC Bioinformatics (2008) doi:10.1186/1471-2105-9-482
David Dao, Adam Fraser, David Stirling, Pearl Ryder, Beth Cimini, Vebjorn Ljosa, Thouis R. Jones, Jane Hung, Shantanu Singh, Mark Bray, Lee Kamentsky, Anne Carpenter
David Logan, Allen Goodman, Alison Kozol, Mohammad Hossein Rohban
Copyright 2021, The Broad Institute of MIT and Harvard. Distributed under the BSD license.