Title
Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis
Abstract
Cellular and subcellular spatial colocalization of structures and molecules in biological specimens is an important indicator of their co-compartmentalization and interaction. Presently, colocalization in biomedical images is addressed with visual inspection and quantified by co-occurrence and correlation coefficients. However, such measures alone cannot capture the complexity of the interactions, which does not limit itself to signal intensity. On top of the previously developed density distribution maps (DDMs), here, we present a method for advancing current colocalization analysis by introducing co-density distribution maps (cDDMs), which, uniquely, provide information about molecules absolute and relative position and local abundance. We exemplify the benefits of our method by developing cDDMs-integrated pipelines for the analysis of molecules pairs co-distribution in three different real-case image datasets. First, cDDMs are shown to be indicators of colocalization and degree, able to increase the reliability of correlation coefficients currently used to detect the presence of colocalization. In addition, they provide a simultaneously visual and quantitative support, which opens for new investigation paths and biomedical considerations. Finally, thanks to the coDDMaker software we developed, cDDMs become an enabling tool for the quasi real time monitoring of experiments and a potential improvement for a large number of biomedical studies.
Year
DOI
Venue
2021
10.3390/s21196385
SENSORS
Keywords
DocType
Volume
local density, local co-density, co-occurrence, correlation, colocalization quantification, data visualization, fluorescence microscopy, subcellular local image analysis, cancer cell
Journal
21
Issue
ISSN
Citations 
19
1424-8220
0
PageRank 
References 
Authors
0.34
0
7