Image3C, a multimodal image-based and label independent integrative method for single-cell analysis
- Stowers Institute for Medical Research, United States
Abstract
Image-based cell classification has become a common tool to identify phenotypic changes in cell populations. However, this methodology is limited to organisms possessing well characterized species-specific reagents (e.g., antibodies) that allow cell identification, clustering and convolutional neural network (CNN) training. In the absence of such reagents, the power of image-based classification has remained mostly off-limits to many research organisms. We have developed an image-based classification methodology we named Image3C (Image-Cytometry Cell Classification) that does not require species-specific reagents nor pre-existing knowledge about the sample. Image3C combines image-based flow cytometry with an unbiased, high-throughput cell cluster pipeline and CNN integration. Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and to detect changes in cellular composition between different conditions. Therefore, Image3C expands the use of imaged-based analyses of cell population composition to research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.
Data availability
All original data underlying this manuscript can be accessed from the Stowers Original Data Repository at http://www.stowers.org/research/publications/libpb-1390. Image3C code and description are freely available at the GitHub repository https://github.com/stowersinstitute/LIBPB-1390-Image3C.
Article and author information
Author details
Alejandro Sánchez Alvarado
Funding
Howard Hughes Medical Institute
- Alejandro Sánchez Alvarado
National Science Foundation (1923372)
- Nicolas Rohner
National Institutes of Health (GM127872,DP2DP2AG071466)
- Nicolas Rohner
Stowers Institute for Medical Research
- Andrew C Box
- Christopher Wood
- Alejandro Sánchez Alvarado
- Nicolas Rohner
Deutsche Forschungsgemeinschaft (PE 2807/1-1)
- Robert Peuß
American Association for Anatomy
- Alice Accorsi
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: Research and animal care were approved by the Institutional Animal Care and Use Committee (IACUC) of the Stowers Institute for Medical Research. protocol (#2019-080)
Copyright
© 2021, Accorsi et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Image3C, a multimodal image-based and label independent integrative method for single-cell analysis
eLife 10:e65372.
https://doi.org/10.7554/eLife.65372
