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

dc.contributor.authorTheart, Rensu P.en_ZA
dc.contributor.authorLoos, Benen_ZA
dc.contributor.authorNiesler, Thomas R.en_ZA
dc.date.accessioned2020-03-11T11:26:12Z
dc.date.available2020-03-11T11:26:12Z
dc.date.issued2019-11-11
dc.identifier.citationTheart, 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
dc.identifier.issn1932-6203 (online)
dc.identifier.otherdoi:10.1371/journal.pone.0225141
dc.identifier.urihttp://hdl.handle.net/10019.1/107611
dc.descriptionCITATION: 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.
dc.descriptionThe original publication is available at https://journals.plos.org/plosone
dc.descriptionPublication of this article was funded by the Stellenbosch University Open Access Fund.
dc.description.abstractENGLISH 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.en_ZA
dc.description.urihttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225141
dc.format.extent21 pages : illustrationsen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherPublic Library of Scienceen_ZA
dc.subjectColocalisationen_ZA
dc.subjectRegression analysisen_ZA
dc.subjectFluorescence microscopyen_ZA
dc.titleRegression adjusted colocalisation colour mapping (RACC) : a novel biological visual analysis method for qualitative colocalisation analysis of 3D fluorescence micrographsen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthors retain copyrighten_ZA


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