The advent of single molecule localization microscopy (SMLM), where individual molecules are serially imaged and their spatial coordinates recorded, allows for the imaging and characterization of structural details in biological samples below the classical diffraction limit. While this technique is capable of creating images with structural detail in the tens of nanometer range, the images generated in SMLM are a computer-generated reconstruction of the localization data. In SMLM, the inherent strength in this imaging modality lies in the quantitative nature of the underlying data. Standard quantitative analysis in other microscopy modalities requires analysis on a conventional image, while SMLM allows for direct statistical analysis on the underlying data.
The field of single molecule localization microscopy is now entering a maturation phase, where the growth and development is happening less within the sphere of novel imaging but rather in the realm of in-depth examination of SMLM data. The comprehensive review paper by Nicovich, Owen, and Gaus aptly cover the rich and diverse area of SMLM quantitative statistical analysis developed by the research field in the past ten years. This paper covers the initial developments of SMLM imaging, and highlights the various analytical domains and the types of experiments and biologically relevant information that can be distracted from this type of imaging modality. This paper covers the most impactful analysis methods currently used within the research community, areas in where they are applicable to extracting biological information, and how the full extent of the data structure of SMLM can be best utilized. This is a comprehensive review paper for a researcher beginning to utilize SMLM for their research, giving numerous examples and methods that can be applied to imaging data to allow direct hypothesis testing in experimental biology.