Extracting quantitative information from single-molecule super-resolution imaging data with LAMA – LocAlization Microscopy Analyzer
Sebastian Malkusch and Mike Heilemann
Single Molecule Biophysics, Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Max-von-Laue-Str. 7, 60438 Frankfurt, Germany
Single-molecule localization microscopy (SMLM) enables studies on the molecular organization of proteins in the cellular context. We introduce the LocAlization Microscopy Analyzer (LAMA), a comprehensive software tool that extracts quantitative information from single-molecule super-resolution imaging data (Malkusch, Heilemann 2016). LAMA allows the characterization of cellular features by size, shape, density and stoichiometry. LAMA uses coordinate-based algorithms such as density-based spatial clustering of applications with noise (DBSCAN) (Ester et al. 1996) and coordinate-based colocalization (CBC) (Malkusch et al. 2012). Additional tools include an automated bead detection for multi-channel registration (Zessin et al. 2013) and a nearest-neighbor analysis (NeNA) to estimate the localization precision (Endesfelder, Heilemann 2014).
Availability and implementation
LAMA is written in python and published open source under GNU publishing license version 3 or later. The source code is freely available from the single-molecule localization microscopy (SMLM) project page at
Pre-compiled versions of the code can be obtained here:
A documentation on the usage of LAMA can be obtained via the following links:
Single-Molecule Biophysics — Single-Molecule Localization Microscopy — software — data science — clustering — localization precision
Endesfelder, Ulrike; Heilemann, Mike (2014): Art and artifacts in single-molecule localization microscopy: beyond attractive images. In Nature methods 11 (3), pp. 235–238. DOI: 10.1038/nmeth.2852.
Ester, Martin; Kriegel, Hans-Peter; Sander, Jörg; Xu, Xiaowei (1996): A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise: AAAI Press.
Malkusch, Sebastian; Endesfelder, Ulrike; Mondry, Justine; Gelléri, Márton; Verveer, Peter J.; Heilemann, Mike (2012): Coordinate-based colocalization analysis of single-molecule localization microscopy data. In Histochemistry and cell biology 137 (1), pp. 1–10. DOI: 10.1007/s00418-011-0880-5.
Malkusch, Sebastian; Heilemann, Mike (2016): Extracting quantitative information from single-molecule super-resolution imaging data with LAMA - LocAlization Microscopy Analyzer. In Scientific reports 6, p. 34486. DOI: 10.1038/srep34486.
Zessin, Patrick J. M.; Krueger, Carmen L.; Malkusch, Sebastian; Endesfelder, Ulrike; Heilemann, Mike (2013): A hydrophilic gel matrix for single-molecule super-resolution microscopy. In Opt Nanoscopy 2 (1), p. 4. DOI: 10.1186/2192-2853-2-4.