title: Quantification of fibrous spatial point patterns from single-molecule localization microscopy (SMLM) data.
abstract: BACKGROUND
  Unlike conventional microscopy which produces pixelated images, SMLM produces data in the form of a list of localization coordinates-a spatial point pattern (SPP). Often, such SPPs are analyzed using cluster analysis algorithms to quantify molecular clustering within, for example, the plasma membrane. While SMLM cluster analysis is now well developed, techniques for analyzing fibrous structures remain poorly explored.
  
  
  RESULTS
  Here, we demonstrate a statistical methodology, based on Ripley's K-function to quantitatively assess fibrous structures in 2D SMLM datasets. Using simulated data, we present the underlying theory to describe fiber spatial arrangements and show how these descriptions can be quantitatively derived from pointillist datasets. We also demonstrate the techniques on experimental data acquired using the image reconstruction by integrating exchangeable single-molecule localization (IRIS) approach to SMLM, in the context of the fibrous actin meshwork at the T cell immunological synapse, whose structure has been shown to be important for T cell activation.
  
  
  METHODS
  Freely available on the web at https://github.com/RubyPeters/Angular-Ripleys-K . Implemented in MatLab.
  
  
  BACKGROUND
  dylan.owen@kcl.ac.uk.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: Ruby
authors.initials: R
authors.lastname: Peters
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: Marta
authors.initials: M
authors.lastname: Benthem Muñiz
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: Juliette
authors.initials: J
authors.lastname: Griffié
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: David J
authors.initials: DJ
authors.lastname: Williamson
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: George W
authors.initials: GW
authors.lastname: Ashdown
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: Christian D
authors.initials: CD
authors.lastname: Lorenz
authors.affiliation: Department of Physics and Randall Division of Cell and Molecular Biophysics, King's College London, London, UK.
authors.forename: Dylan M
authors.initials: DM
authors.lastname: Owen
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019169:Jurkat Cells; D000072760:Single Molecule Imaging / Q000379:methods*; D013601:T-Lymphocytes / Q000737:chemistry / Q000378:metabolism