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Analyzing Cell Painting PLUS Data Using Cell Profiler and KNIME Analytics Platform.

Marlene Wedler1,2, Nils Körber3, Shu Liu4

  • 1German Centre for the Protection of Laboratory Animals (Bf3R) and Experimental Toxicology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.

Methods in Molecular Biology (Clifton, N.J.)
|January 1, 2026
PubMed
Summary
This summary is machine-generated.

This study details a CellProfiler pipeline for Cell Painting PLUS (CPP) image analysis, enabling efficient identification of cellular morphology changes. The workflow aids in understanding compound or genetic perturbation effects on organelles.

Keywords:
Benchmark dose modelingCell Painting PLUSCell ProfilerImage analysisKNIMEMorphological profiling

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Area of Science:

  • Cellular and Molecular Biology
  • Bioinformatics
  • High-Content Screening

Background:

  • High-throughput/high-content multiplexed phenotypic (HTS/HCS) screening methods like Cell Painting PLUS (CPP) are crucial for identifying cellular morphology changes.
  • These screens generate vast imaging datasets requiring sophisticated analysis for feature extraction.
  • Open-source tools like CellProfiler and KNIME Analytics Platform facilitate image analysis and data processing.

Purpose of the Study:

  • To present a comprehensive CellProfiler pipeline for analyzing Cell Painting PLUS (CPP) images.
  • To detail the image analysis workflow from illumination correction to feature extraction and processing.
  • To enable efficient summarization of cellular responses to chemical or genetic perturbations.

Main Methods:

  • Developed a CellProfiler pipeline for CPP image analysis, including illumination correction and image registration using 4i stitcher software.
  • Performed cell region segmentation and extracted approximately 3000 morphological features.
  • Utilized KNIME Analytics Platform for data processing, normalization, and benchmark dose modeling.

Main Results:

  • The pipeline successfully processes CPP images, extracting a large number of cellular features.
  • KNIME Analytics Platform facilitates data normalization and dose modeling with minimal coding.
  • Visualization tools like accumulation and magnitude plots effectively summarize responsive features and affected organelles.

Conclusions:

  • The presented CellProfiler pipeline offers a robust method for analyzing CPP imaging data.
  • This approach aids researchers in identifying cellular targets affected by compounds or genetic modifications.
  • The workflow enhances the utility of HTS/HCS screens for biological discovery.