The recent development of super-resolution techniques and particularly of single molecule localisation microscopy (SMLM), techniques like PALM and dSTORM allow the precise localisation of individual molecules in densely packed protein structures and can be used to characterise the spatial organisation of proteins. Most cellular functions involve multiple components; therefore multi-colour SMLM is an essential tool to address how interactions between different proteins determine biological function. In contrast with conventional fluorescence microscopy where image-based analysis is applied to quantify colocalisation, coordinate-based microscopy needs new strategies to quantify the association of molecules within the same structure.
In recent years, methodologies have been proposed to quantify dual colour SMLM data. However, none of them satisfyingly incorporates an evaluation of the spatial distribution and the quantification of the correlation between two channels. Molecular mechanisms such as T cell signalling  or focal adhesion formation, where a large number of proteins are recruited to a specific site, would benefit from having both types of information available.
Here, we present a new analysis method to simultaneously quantify the degree of clustering and co-clustering in two-colour SMLM experiments. This method takes advantage of a cluster detection combined with a nearest neighbour analysis and a coordinate-based colocalisation coefficient. We demonstrate the viability of this approach on different biological systems (T cell signalling and focal adhesions) to correlate the molecular density of clusters with the degree of co-clustering. Finally, we show that this method is able to identify different populations of clusters based on their size, density and degree of co-clustering. For each population we reveal the internal structure and organisation of different proteins inside the clusters at a nanometric scale.