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Single-molecule localization microscopy (SMLM) relies on the temporarily separated emission of individual molecules. While the acquired image is still diffraction limited, due to their sparsity, individual molecules can be localized at nanometer precision and their coordinates accumulated to form a super-resolved image. But the power of SMLM goes far beyond generating images. Computational analysis tools allow extracting the spatial organization, colocalization, clustering, and dynamics of individual molecules, which has transformed the study of nanoscale biology over the past decade. This wiki gives an introduction to SMLM and mostly practical information to get you started with your own experiments or data analysis. Please note that SMLM (as most microscopy analysis workflows) data analysis is very user-dependent and varies with the experiment, the type of imaging or the measurable quantity. These pages only describe some options and the examples are by no means exhaustive.
Start here for a brief introduction into SMLM.
This section gives an introduction into a typical SMLM data analysis workflow starting from localization over filtering to image reconstruction. The correction of sample drift and chromatic aberrations are also discussed.
This section describes how to perform a single-molecule calibration experiment and provides some scripts to extract quantitative information. I provide and demonstrate analysis of a test dataset of Alexa647-labelled antibodies. Blinking characteristics can be used in the following to group (merge) blinking events and estimate molecule quantities.
Here you'll see how to perform a basic spatial analysis using simple density-based clustering and refer to more complex analysis schemes.
The tracking page describes how to link molecule positions between frames to extract molecule diffusion properties from live-cell experiments.
Simulations can be very helpful when developing a new analysis routine or simply to shape your expectations of a certain structure you want to image.
SMLM would not be possible without the right software tools. A number of excellent open-source software platforms are available through the SMLM community. While I provide some of my personal analysis scripts in this repository, I summarize what else is available and give main applications.
If you want to know more you’ll find references here and throughout the other sections.