Unbiased and robust analysis of co-localization in super-resolution images.

ABSTRACT: Spatial data from high-resolution images abound in many scientific disciplines. For example, single-molecule localization microscopy, such as stochastic optical reconstruction microscopy, provides super-resolution images to help scientists investigate co-localization of proteins and hence their interactions inside cells, which are key events in living cells. However, there are few accurate methods for analyzing co-localization in super-resolution images. The current methods and software are prone to produce false-positive errors and are restricted to only 2-dimensional images. In this paper, we develop a novel statistical method to effectively address the problems of unbiased and robust quantification and comparison of protein co-localization for multiple 2- and 3-dimensional image dataset

SUBMITTER: Liu X 

PROVIDER: S-EPMC9648350 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature