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Superresolution microscopy analysis platform

COPYRIGHT: Jonas Ries, 2020 LICENSE: GPLv3 AUTHOR: Jonas Ries, EMBL Heidelberg, 27.03.2020, PLEASE CITE AS: Ries, J. SMAP: a modular super-resolution microscopy analysis platform for SMLM data. Nat Methods (2020). Please also cite the references for the plugins you use (as mentioned in the plugin info).

Documentation and installation instructions at: /Documents/Manual/ Instructions for using SMAP to analyze nuclear pore complex standard samples: /Documentation/Manual/SMAP_manual_NPC.pdf

Please cite as: Ries, J. SMAP: a modular super-resolution microscopy analysis platform for SMLM data. Nature Methods (2020) doi:10.1038/s41592-020-0938-1.


  1. MATLAB 2019a and newer. Toolboxes: Optimization, Image processing, Curve fitting, Statistics and Machine Learning. A fully functional stand-alone version that does not require a MATLAB license but is limited in extendability can be downloaded from (Installation notes see below).

  2. Mac or Windows

  3. For GPU fitting: Windows, NVIDIA graphics card. CUDA driver (recommended: version 7.5). All fitters also come with a CPU version that is used when these specifications are not met.


  1. Clone git repository:

    a. Use Terminal (MacOS) or Cmd (Win). Use cd to navigate to the target directory. (e.g. cd git)

    b. Type: git clone and type in your username and password for your git account.

  2. Install Micromanager 1.4.22 from

  3. If needed install

  4. In MATLAB: run SMAP.m, if questioned, change folder.

  5. In the Menu select SMAP/Preferences... Switch to the Directories tab and select the directories of Micro-Manager and of the bioformats_package.jar. Press Save and exit.

Typical install times: 15 minutes.

Installation of stand-alone version

  1. Download the respective version from corresponding to your operating system.
  2. Follow the installation notes in Installation_notes_SMAP_compiled.rtf which can be found under the previous link.