Topological data analysis quantifies biological nano-structure from single molecule localization microscopy.

ABSTRACT: MOTIVATION:Localization microscopy data is represented by a set of spatial coordinates, each corresponding to a single detection, that form a point cloud. This can be analyzed either by rendering an image from these coordinates, or by analyzing the point cloud directly. Analysis of this type has focused on clustering detections into distinct groups which produces measurements such as cluster area, but has limited capacity to quantify complex molecular organization and nano-structure. RESULTS:We present a segmentation protocol which, through the application of persistence-based clustering, is capable of probing densely packed structures which vary in scale. An increase in segmentation performance over state-of-the-art methods is demonstrated. Moreover we employ persistent homology to move b

SUBMITTER: Pike JA 

PROVIDER: S-EPMC7162425 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature