Co-localization analysis in fluorescence microscopy via maximum entropy copula

Farsani, Zahra Amini und Schmid, Volker J. (18. September 2020): Co-localization analysis in fluorescence microscopy via maximum entropy copula. In: The International Journal of Biostatistics

Abstract

Co-localization analysis is a popular method for quantitative analysis in fluorescence microscopy imaging. The localization of marked proteins in the cell nucleus allows a deep insight into biological processes in the nucleus. Several metrics have been developed for measuring the co-localization of two markers, however, they depend on subjective thresholding of background and the assumption of linearity. We propose a robust method to estimate the bivariate distribution function of two color channels. From this, we can quantify their co- or anti-colocalization. The proposed method is a combination of the Maximum Entropy Method (MEM) and a Gaussian Copula, which we call the Maximum Entropy Copula (MEC). This new method can measure the spatial and nonlinear correlation of signals to determine the marker colocalization in fluorescence microscopy images. The proposed method is compared with MEM for bivariate probability distributions. The new colocalization metric is validated on simulated and real data. The results show that MEC can determine co- and anti-colocalization even in high background settings. MEC can, therefore, be used as a robust tool for colocalization analysis.

• Dokumententyp: Zeitschriftenartikel
• Publikationsform: Publisher's Version
• Keywords: computational biology; Gaussian copula; Kendall’s τ; maximum entropy method; nucleonic
• Fakultät: Mathematik, Informatik und Statistik > Statistik ; Mathematik, Informatik und Statistik > Statistik > Lehrstühle/Arbeitsgruppen > Bioimaging
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik ; 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie
• ISSN: 1557-4679
• Sprache: Englisch