A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores
Published in The annals of applied statistics, January 2019
Publisher: NIH Public Access
The manuscript by Patel et al. (2019) introduces the Photo-switching hidden Markov model (PSHMM) for analyzing photo-switching behavior of fluorophores in single molecule localization microscopy. The authors developed a method to link the observations to the continuous time photo-switching behavior using a hidden Markov model, and introduced transmission matrices to capture all dependencies present in the model. They presented a modification of the forward-backward algorithm for estimating the unknown parameters of the PSHMM and demonstrated its effectiveness through simulations and comparisons with exponential fitting. The study also applied the method to real data, providing evidence of a relationship between laser intensity and photo-switching rates and supporting the hypothesis of multiple off-states for Alexa Fluor 647. The PSHMM approach can effectively distinguish between different photo-switching mechanisms and quantify rate constants and photo-switching time distributions, providing valuable insights for optimizing fluorophores' use in super-resolution microscopy and other applications.