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PXPermute reveals staining importance in multichannel imaging flow cytometry
Sayedali Shetab Boushehri1, Aleksandra Kornivetc2, Domink J E Winter3
1Institute of AI for Health, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Institute of Computational Biology, Helmholtz Zentrum MünchenMunich - Helmholtz Munich - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Technical University of Munich, Department of Mathematics, 85748 Munich, Germany; Data & Analytics (D&A), Roche Pharma Research and Early Development (pRED), Roche Innovation Center Munich, 82377 Penzberg, Germany.
PXPermute efficiently identifies key imaging flow cytometry channels for cell analysis. This method reduces experimental costs and time by pinpointing the most informative fluorescent channels, aiding biomarker discovery.
Area of Science:
- Biotechnology
- Computational Biology
- Cell Biology
Background:
- Imaging flow cytometry (IFC) enables high-throughput single-cell image acquisition across multiple fluorescent channels.
- Traditional IFC staining protocols are resource-intensive, time-consuming, and can impact cell viability.
- Optimizing channel selection is critical for efficient downstream analysis and cost reduction in IFC experiments.
Purpose of the Study:
- To introduce PXPermute, a novel method for assessing the significance of individual channels in IFC data.
- To provide a user-friendly tool for optimizing experimental design and channel selection in cell profiling studies.
- To reduce the cost and complexity associated with IFC data analysis.
Main Methods:
- PXPermute evaluates channel importance by systematically permuting pixel values within each channel.
- The impact of pixel permutation on machine learning and deep learning models is analyzed to determine channel significance.
- The method was validated using three distinct multichannel IFC image datasets.
Main Results:
- PXPermute accurately identified the most informative channels across diverse IFC datasets.
- The identified channels aligned with existing biological knowledge, confirming the method's reliability.
- The study demonstrated the potential for PXPermute to streamline experimental workflows.
Conclusions:
- PXPermute offers a robust and efficient approach for channel selection in IFC analysis.
- The method facilitates systematic channel analysis, aiding biologists in experimental design and optimization.
- PXPermute supports biomarker identification and enhances the overall utility of IFC for cell profiling.
