@article {70257,
	title = {Redefining colocalization analysis with a novel phasor mixing coefficient},
	journal = {Journal of Cell Science},
	volume = {139},
	year = {2026},
	month = {2026 Jan 19},
	pages = {jcs264388},
	abstract = {<p>The first step to probing any potential interaction between two biomolecules is to determine their spatial association. In other words, if two biomolecules localize similarly within a cell, then it is plausible they could interact. Traditionally, this is quantified through various colocalization metrics. These measures infer this association by estimating the degree to which fluorescent signals from each biomolecule overlap or correlate. However, these metrics are, at best, proxies, and they depend strongly on various experimental choices. Here, we define a new strategy that leverages multispectral imaging and phasor analysis, termed the phasor mixing coefficient (PMC). The PMC measures the precise mixing of fluorescent signals in each pixel. We demonstrate how the PMC captures complex biological subtlety by offering two distinct values, a global measure of overall color mixing and the homogeneity thereof. We additionally show that the PMC exhibits less sensitivity to signal-to-noise ratio, intensity threshold and background signal compared to canonical methods. Moreover, this method provides a means to visualize color mixing at each pixel. We show that the PMC offers users a nuanced and robust metric to quantify biological association.</p>
},
	issn = {0021-9533},
	doi = {10.1242/jcs.264388},
	url = {https://doi.org/10.1242/jcs.264388},
	author = {Puls, Owen F. and Aaron, Jesse S. and Quarles, Ellen K. and Khuon, Satya and Eisenman, Leanna R. and Kamaid, Andres and Malacrida, Leonel and Chew, Teng-Leong}
}
