Software for correction, evaluation and visualization of single-molecule localization microscopy (SMLM) data. SharpViSu user manual
SharpViSu 2 also includes:
• SplitViSu for spectral demixing of SMLM data, acquired with a dichroic image splitter: SplitViSu user manual
• ClusterViSu for cluster analysis of SMLM data using Voronoi diagrams and Ripley functions: ClusterViSu user manual
The software can be used either as a standalone application for Windows or as an application for MATLAB
Standalone SharpViSu with SplitViSu & ClusterViSu for Windows (recommended):
Download and run the latest version of “Installer/SharpViSu_web_installer.exe” and follow instructions. If not already installed, the MATLAB Compiler Runtime (mcr) will be downloaded from the web and installed automatically.
Standalone SplitViSu or ClusterViSu for Windows:
Download and run the latest version of “Installer/SplitViSu_web_installer.exe or ”Installer/ClusterViSu_web_installer.exe" and follow instructions. If not already installed, the MATLAB Compiler Runtime (mcr) will be downloaded from the web and installed automatically.
MATLAB application & source code (works under your MATLAB environment):
Please use MATLAB R2021b for optimal performance of SplitViSu! In newer MATLAB versions there is a bug that makes it difficult to modify ROIs within the GUI.
Add folder “SharpViSu” to your MATLAB search path. SharpViSu v2 was developed in MATLAB R2021b. Toolboxes required: Image Processing Toolbox, Signal Processing Toolbox, Statistics and Machine Learning Toolbox.
User manual for spectral demixing of SMLM data in SplitViSu
Test data for spectral demixing in SplitViSu
Andronov, L., Lutz, Y., Vonesch, J.-L. & Klaholz, B. P. SharpViSu: integrated analysis and segmentation of super-resolution microscopy data. Bioinformatics (2016) doi:10.1093/bioinformatics/btw123
Andronov, L., Orlov, I., Lutz, Y., Vonesch, J.-L. & Klaholz, B. P. ClusterViSu, a method for clustering of protein complexes by Voronoi tessellation in super-resolution microscopy. Scientific Reports 6, 24084 (2016) http://www.nature.com/articles/srep24084
Andronov L., Michalon J., Ouararhni K., Orlov I., Hamiche A., Vonesch J-L, Klaholz B.P. 3DClusterViSu: 3D clustering analysis of super-resolution microscopy data by 3D Voronoi tessellations. Bioinformatics 34 (2018) https://doi.org/10.1093/bioinformatics/bty200
Andronov, L., Genthial, R., Hentsch, D., & Klaholz, B. P. splitSMLM, a spectral demixing method for high-precision multi-color localization microscopy applied to nuclear pore complexes. Commun. Biol. (2022) https://doi.org/10.1038/s42003-022-04040-1
Andronov, L., Ouararhni, K., Stoll, I., Klaholz, B.P., Hamiche, A. CENP-A nucleosome clusters form rosette-like structures around HJURP during G1. Nat. Commun. 10, 4436 (2019) https://doi.org/10.1038/s41467-019-12383-3
Lemaître, C., Grabarz, A., Tsouroula, K., Andronov, L., Furst, A., Pankotai, T., Heyer, V., Rogier, M., Attwood, K M., Kessler, P., Dellaire, G., Klaholz, B., Reina-San-Martin, B., Soutoglou, E. Nuclear position dictates DNA repair pathway choice. Genes. Dev. 28, 2450-2463 (2014) https://doi.org/10.1101/gad.248369.114
Andronov L., Vonesch J-L, Klaholz B.P. Practical Aspects of Super-Resolution Imaging and Segmentation of Macromolecular Complexes by dSTORM. In: Poterszman A. (eds) Multiprotein Complexes. Methods in Molecular Biology, 2247 271-286 (2021) Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1126-5_15
Andronov, L., Genthial, R., Hentsch, D., & Klaholz, B. P. splitSMLM, a spectral demixing method for high-precision multi-color localization microscopy applied to nuclear pore complexes. Commun. Biol. (2022) https://doi.org/10.1038/s42003-022-04040-1