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DAOSTORM: an algorithm for high- density super-resolution microscopy

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Figure 1: Comparison of DAOSTORM to existing super-resolution localization algorithms.

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Acknowledgements

We thank K. Finan, S. Baboo and P.R. Cook (University of Oxford) for COS-7 cells, and S. van de Linde, U. Endesfelder, M. Heilemann and M.A. Little for technical assistance. S.J.H., S.U. and A.N.K. were supported by Biotechnology and Biological Sciences Research Council grant BB/H0179SX/1 and Bionanotechnology Interdisciplinary Research Collaboration grant GR/R45659/01. This research was funded by the EU Seventh Framework Programme (FP7/2007-2013; grant 201418, READNA). S.U. was supported by MathWorks, USA.

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  1. Department of Physics, Biological Physics Research Group, Clarendon Laboratory, University of Oxford, Oxford, UK

    Seamus J Holden, Stephan Uphoff & Achillefs N Kapanidis

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  1. Seamus J Holden
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  2. Stephan Uphoff
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  3. Achillefs N Kapanidis
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Correspondence to Seamus J Holden or Achillefs N Kapanidis.

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Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Methods, Supplementary Discussion, Supplementary Note (PDF 795 kb)

Supplementary Software

The DAOSTORM software, a user's manual, installation instructions, test data and a licensing agreement. (ZIP 352 kb)

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Holden, S., Uphoff, S. & Kapanidis, A. DAOSTORM: an algorithm for high- density super-resolution microscopy. Nat Methods 8, 279–280 (2011). https://doi.org/10.1038/nmeth0411-279

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