ArticleBMC bioinformatics2019
SMoLR: visualization and analysis of single-molecule localization microscopy data in R.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Distinct mobility patterns of BRCA2 molecules at DNA damage sites.Nucleic acids research · 2024Article
- Compartmentalization of androgen receptors at endogenous genes in living cells.Nucleic acids research · 2023Article
- Three-color dSTORM Imaging and Analysis of Recombination Foci in Mouse Spread Meiotic Nuclei.Bio-protocol · 2023Article
- Multi-color dSTORM microscopy in Hormad1-/- spermatocytes reveals alterations in meiotic recombination intermediates and synaptonemal complex structure.PLoS genetics · 2022Article
- Can super-resolution microscopy become a standard characterization technique for materials chemistry?Chemical science · 2022Review
- Measuring Nanoscale Distances by Structured Illumination Microscopy and Image Cross-Correlation Spectroscopy (SIM-ICCS).Sensors (Basel, Switzerland) · 2021Article
- A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods.Patterns (New York, N.Y.) · 2020Review
- Super-resolution imaging of RAD51 and DMC1 in DNA repair foci reveals dynamic distribution patterns in meiotic prophase.PLoS genetics · 2020Article
- Redundant and specific roles of cohesin STAG subunits in chromatin looping and transcriptional control.Genome research · 2020Article
- Review
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Authors and funding
7 authors.
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Abstract
backgroundSingle-molecule localization microscopy is a super-resolution microscopy technique that allows for nanoscale determination of the localization and organization of proteins in biological samples. For biological interpretation of the data it is essential to extract quantitative information from the super-resolution data sets. Due to the complexity and size of these data sets flexible and user-friendly software is required.
resultsWe developed SMoLR (Single Molecule Localization in R): a flexible framework that enables exploration and analysis of single-molecule localization data within the R programming environment. SMoLR is a package aimed at extracting, visualizing and analyzing quantitative information from localization data obtained by single-molecule microscopy. SMoLR is a platform not only to visualize nanoscale subcellular structures but additionally provides means to obtain statistical information about the distribution and localization of molecules within them. This can be done for individual images or SMoLR can be used to analyze a large set of super-resolution images at once. Additionally, we describe a method using SMoLR for image feature-based particle averaging, resulting in identification of common features among nanoscale structures.
conclusionsEmbedded in the extensive R programming environment, SMoLR allows scientists to study the nanoscale organization of biomolecules in cells by extracting and visualizing quantitative information and hence provides insight in a wide-variety of different biological processes at the single-molecule level.
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