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).
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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.
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