Data-analysis strategies for image-based cell profiling

Juan C. Caicedo, Sam Cooper, Florian Heigwer, Scott Warchal, Peng Qiu, Csaba Molnar, Aliaksei S. Vasilevich, Joseph D. Barry, Harmanjit Singh Bansal, Oren Kraus, Mathias Wawer, Lassi Paavolainen, Markus D. Herrmann, Mohammad Rohban, Jane Hung, Holger Hennig, John Concannon, Ian Smith, Paul A. Clemons, Shantanu SinghPaul Rees, P. Horváth, Roger G. Linington, Anne E. Carpenter

Research output: Article

126 Citations (Scopus)

Abstract

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.

Original languageEnglish
Pages (from-to)849-863
Number of pages15
JournalNature Methods
Volume14
Issue number9
DOIs
Publication statusPublished - aug. 31 2017

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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  • Cite this

    Caicedo, J. C., Cooper, S., Heigwer, F., Warchal, S., Qiu, P., Molnar, C., Vasilevich, A. S., Barry, J. D., Bansal, H. S., Kraus, O., Wawer, M., Paavolainen, L., Herrmann, M. D., Rohban, M., Hung, J., Hennig, H., Concannon, J., Smith, I., Clemons, P. A., ... Carpenter, A. E. (2017). Data-analysis strategies for image-based cell profiling. Nature Methods, 14(9), 849-863. https://doi.org/10.1038/nmeth.4397