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Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy

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Imaging Cell Signaling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2800))

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Abstract

High-throughput microscopy has enabled screening of cell phenotypes at unprecedented scale. Systematic identification of cell phenotype changes (such as cell morphology and protein localization changes) is a major analysis goal. Because cell phenotypes are high-dimensional, unbiased approaches to detect and visualize the changes in phenotypes are still needed. Here, we suggest that changes in cellular phenotype can be visualized in reduced dimensionality representations of the image feature space. We describe a freely available analysis pipeline to visualize changes in protein localization in feature spaces obtained from deep learning. As an example, we use the pipeline to identify changes in subcellular localization after the yeast GFP collection was treated with hydroxyurea.

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Acknowledgments

We thank members of the Moses lab for their input. The analysis reported here was performed on infrastructure obtained with grants to AMM from the Canadian Foundation for Innovation (CFI) AMM is supported by a Canada Research Chair.

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Authors and Affiliations

  1. Microsoft Research New England, Cambridge, MA, USA

    Alex X. Lu

  2. Department of Cell & Systems Biology, University of Toronto, Toronto, Canada

    Alan M. Moses

Authors
  1. Alex X. Lu
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  2. Alan M. Moses
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Corresponding author

Correspondence to Alex X. Lu .

Editor information

Editors and Affiliations

  1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK

    Christoph Wuelfing

  2. Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA

    Robert F. Murphy

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© 2024 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Lu, A.X., Moses, A.M. (2024). Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy. In: Wuelfing, C., Murphy, R.F. (eds) Imaging Cell Signaling. Methods in Molecular Biology, vol 2800. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3834-7_15

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  • DOI: https://doi.org/10.1007/978-1-0716-3834-7_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3833-0

  • Online ISBN: 978-1-0716-3834-7

  • eBook Packages: Springer Protocols

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