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Analyzing high-throughput experiments often requires computer programming skills that are beyond the range of most biologists. Knime makes it easier to mine such data, but lacks common methods necessary for screen mining. Thus, we’ve implemented a set of Knime nodes called HCS Tools. It includes readers for various microscopes, quality controls metrics, all common plate normalization methods, library annotation tools, as well as barcode and plate layout utilities. Finally there is a very powerful Plate-Heatmap-Viewer to quickly get an overview of your screen.
Together with a rich set of R templates for visualization and modeling, these tools provide a powerful solution for mining screening data that is easy to use, but flexible enough to cope with various types of assays.
The latest version the HCS Tools is available from the Knime community repository. To install them, just add the community update site url to Knime and select the scripting extensions from the list.
The HCS Tools are released under the 3-clause BSD License.
Feel welcome to contact us if you want to contribute to this project, have suggestions, found bugs, or want to tell us about your vision about screen mining software.
Please acknowledge or cite this website if you have used this KNIME extension in your work and found it helpful:
https://github.com/knime-mpicbg/HCS-Tools/wiki
If you want to mention our institution use this:
High-Throughput Technology Development Studio (TDS) Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG)
We have published a book chapter (Springer, PubMed) on open source software tools for high-content screening, where we introduced the Scripting Integration and HCS-Tools for KNIME. Feel free to add this as a citation. Here is the citation in BibTeX format:
@incollection{
year={2013},
isbn={978-1-62703-310-7},
booktitle={Target Identification and Validation in Drug Discovery},
volume={986},
series={Methods in Molecular Biology},
editor={Moll, Jurgen and Colombo, Riccardo},
doi={10.1007/978-1-62703-311-4_8},
title={CellProfiler and KNIME: Open Source Tools for High Content Screening},
url={http://dx.doi.org/10.1007/978-1-62703-311-4_8},
publisher={Humana Press},
keywords={High content screening; Image processing; Statistics; Open Source; CellProfiler; KNIME; Distributed computing},
author={Stöter, Martin and Niederlein, Antje and Barsacchi, Rico and Meyenhofer, Felix and Brandl, Holger and Bickle, Marc},
pages={105-122},
language={English}
}