ABSTRACTLocalization-based super-resolution microscopy techniques such as PALM, STORM, and PAINT are increasingly critical tools for biological discovery. These methods generate lists of single fluorophore positions that capture nanoscale structural details of subcellular organisation, but to develop biological insight, we must post-process and visualize this data in a meaningful way. A large number of algorithms have been developed for localization post-processing, transforming point data into representations which approximate traditional microscopy images, and performing specific quantitative analysis directly on points. Implementations of these algorithms typically stand in isolation, necessitating complex workflows involving multiple different software packages. Here we present PYMEVisualize, an open-source tool for the interactive exploration and analysis of 3D, multicolor, single-molecule localization data. PYMEVisualize brings together a broad range of the most commonly used post-processing, density mapping, and direct quantification tools in an easy-to-use and extensible package. This software is one component of the PYthon Microscopy Environment (python-microscopy.org), an integrated application suite for light microscopy acquisition, data storage, visualization, and analysis built on top of the scientific Python environment.
A Free, Open-Source Tool for Identifying Urban Agglomerations using Point Data
