Regression adjusted colocalisation colour mapping (RACC) : a novel biological visual analysis method for qualitative colocalisation analysis of 3D fluorescence micrographs

Date
2019-11-11
Journal Title
Journal ISSN
Volume Title
Publisher
Public Library of Science
Abstract
ENGLISH ABSTRACT: The qualitative analysis of colocalisation in fluorescence microscopy is of critical importance to the understanding of biological processes and cellular function. However, the degree of accuracy achieved may differ substantially when executing different yet commonly utilized colocalisation analyses. We propose a novel biological visual analysis method that determines the correlation within the fluorescence intensities and subsequently uses this correlation to assign a colourmap value to each voxel in a three-dimensional sample while also highlighting volumes with greater combined fluorescence intensity. This addresses the ambiguity and variability which can be introduced into the visualisation of the spatial distribution of correlation between two fluorescence channels when the colocalisation between these channels is not considered. Most currently employed and generally accepted methods of visualising colocalisation using a colourmap can be negatively affected by this ambiguity, for example by incorrectly indicating non-colocalised voxels as positively correlated. In this paper we evaluate the proposed method by applying it to both synthetic data and biological fluorescence micrographs and demonstrate how it can enhance the visualisation in a robust way by visualising only truly colocalised regions using a colourmap to indicate the qualitative measure of the correlation between the fluorescence intensities. This approach may substantially support fluorescence microscopy applications in which precise colocalisation analysis is of particular relevance.
Description
CITATION: Theart, R. P., Loos, B. & Niesler, T. R. 2019. Regression adjusted colocalisation colour mapping (RACC) : a novel biological visual analysis method for qualitative colocalisation analysis of 3D fluorescence micrographs. PLoS ONE 14(11):e0225141, doi:10.1371/journal.pone.0225141.
The original publication is available at https://journals.plos.org/plosone
Publication of this article was funded by the Stellenbosch University Open Access Fund.
Keywords
Colocalisation, Regression analysis, Fluorescence microscopy
Citation
Theart, R. P., Loos, B. & Niesler, T. R. 2019. Regression adjusted colocalisation colour mapping (RACC) : a novel biological visual analysis method for qualitative colocalisation analysis of 3D fluorescence micrographs. PLoS ONE 14(11):e0225141, doi:10.1371/journal.pone.0225141