Over the last decade, single-molecule localization microscopy (SMLM) has revolutionized cell biology, making it possible to monitor molecular organization and dynamics with spatial resolution of a few nanometers. By identifying the molecule coordinates instead of producing images, SMLM holds an important paradigm shift towards conventional fluorescence microscopy. Consequently, dedicated analyzing tools and methods have been developed to properly quantify SMLM data. In this workshop we will present various analytical methods designed to quantify single-molecule localization microscopy (SMLM) data directly from the localization coordinates. In particular, we will review clustering, segmentation and colocalization methods, for both 2D and 3D SMLM data. This workshop will focus on various state of the art methods that use localization coordinates for quantification. In particular, we will present: • Clustering o K-Ripley function • Segmentation o DBSCAN o SR-Tesseler • Colocalization o CBC (Coordinate-Based Colocalization) o Clus-DoC o Coloc-Tesseler The participants will apply those techniques on custom simulations, experimental data (microtubules in 2D and 3D, mitochondria, synaptic proteins, adhesion site) as well as datasets acquired during MiFoBio when possible. We will also discuss how experimental parameters, such as blinking, photoactivation, labelling efficiency, drift and chromatic aberration, can affect the quantifications and how they can be taken into account. All the exercises will be performed on Point Cloud Analyst (PoCA), a new intuitive software platform that can handle multidimensional SMLM data.