Abstract
Super-resolution microscopy allows imaging of cellular structures with high throughput and detail. However, the efficient and quantitative analysis of images generated is challenging with existing tools. Here, we develop ASAP (automated structures analysis program) to enable rapid and automated detection, classification and quantification of super-resolved structures. We validate ASAP on ground truth data and demonstrate its broad applicability by analyzing images of nucleoporins, TORC1 complexes, endocytic vesicles and Bax pores.
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Data availability
The data that support the findings of this study are available from the corresponding authors upon request.
Code availability
Updated versions and source code for ASAP can be obtained from https://github.com/jdanial/ASAP. Compliations of ASAP for Windows and MacOS are available as Supplementary Software.
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Acknowledgements
We would like to thank C. Sieben and S. Manley (Ecole polytechnique fédérale de Lausanne, EPFL) for providing super-resolved images of TORC1, M. Mund and J. Ries (European Molecular Biology Laboratory, EMBL) for data sets of proteins involved in clathrin-mediated endocytosis and useful discussions, R. Salvador-Gallego (University of Colorado Boulder) for helpful discussions on the data sets of the apoptotic protein Bax, and S. Alexander and J. Ellenberg (EMBL) for super-resolved images of nucleoporins. We acknowledge a Max Planck Society (Max-Planck-Gesellschaft) postdoctoral fellowship, awarded to J.S.H.D. This work was supported by Deutsche Forschungsgemeinschaft (DFG) grant GA164/3-1 and the European Research Council (ERC) starting grant 309966 awarded to A.J.G.S.
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Authors and Affiliations
Contributions
J.S.H.D. and A.J.G.S. conceived and designed the study, J.S.H.D. wrote the software and performed the analysis. J.S.H.D. and A.J.G.S. assessed performance and wrote the manuscript.
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Peer review information: Rita Strack was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
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Supplementary information
Supplementary Information
Supplementary Notes 1–7
Supplementary Software
ASAP v1.0 Software
Supplementary Software Guides
User manual, description of parameters, errors and warnings messages syntax, automation script syntax, methodology and workflow.
User and Software Examples
User manual examples, description of parameters examples and automation script examples.
Supplementary Data
Supplementary source data for figures within Supplementary Notes.
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Danial, J.S.H., Garcia-Saez, A.J. Quantitative analysis of super-resolved structures using ASAP. Nat Methods 16, 711–714 (2019). https://doi.org/10.1038/s41592-019-0472-1
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DOI: https://doi.org/10.1038/s41592-019-0472-1
Further reading
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Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning
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