  As camera pixel arrays have grown larger and faster, and optical microscopy
techniques ever more refined, there has been an explosion in the quantity of
data acquired during routine light microcopy. At the single-molecule level,
analysis involves multiple steps and can rapidly become computationally
expensive, in some cases intractable on office workstations. Complex bespoke
software can present high activation barriers to entry for new users. Here, we
redevelop our quantitative single-molecule analysis routines into an optimized
and extensible Python program, with GUI and command-line implementations to
facilitate use on local machines and remote clusters, by beginners and advanced
users alike. We demonstrate that its performance is on par with previous MATLAB
implementations but runs an order of magnitude faster. We tested it against
challenge data and demonstrate its performance is comparable to
state-of-the-art analysis platforms. We show the code can extract fluorescence
intensity values for single reporter dye molecules and, using these, estimate
molecular stoichiometries and cellular copy numbers of fluorescently-labeled
biomolecules. It can evaluate 2D diffusion coefficients for the
characteristically short single-particle tracking data. To facilitate
benchmarking we include data simulation routines to compare different analysis
programs. Finally, we show that it works with 2-color data and enables
colocalization analysis based on overlap integration, to infer interactions
between differently labelled biomolecules. By making this freely available we
aim to make complex light microscopy single-molecule analysis more
democratized.
