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Are you approaching colocalization analysis right?

2018.03.14

Right approach to analyze colocalization

Co-occurence and correlation

When analyzing colocalization, you should remember that its quantification,  in fact, describes several visual phenomena, most important of which are co-occurrence and correlation. Co-occurrence estimates the extent of spatial overlap between two fluorophores, while correlation determines the degree to which the extent of two spatially overlapping fluorophores are related to each other. Both estimations have their adverse strengths and weaknesses.

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Different coefficients

Naturally, these two different phenomena are measured by different coefficients. Co-occurrence is estimated by overlap coefficient (R) according to Manders (MOC) and is in the range of values from 0 to 1.  Correlation is estimated by Pearson’s correlation coefficient  (Rr) (PCC) and is in the range of values from -1.0 to 1.0.

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Applicability

The applicability of a particular coefficient depends on the nature of the examined biological processes as well as technical limitations of colocalization experiments. Co-occurrence measurements are often best utilized to determine what proportion of a molecule is present within particular region of interest (ROI), compartment or organelle. It doesn’t give an insight into any concentration relationship between two molecules.  Correlation, on the other hand, is most applicable when assessing functional or stoichiometric relationship between two overlapping molecules. It doesn’t measure the extent of spatial co-occurrence. Co-occurrence and correlation can be observed simultaneously and independently of each other, and the extent of either phenomenon is largely determined by the underlined biological behavior. In addition, it is necessary to consider the properties of analyzed images. MOC values can be erroneously elevated due to out-of-focus light and background fluorescence, while PCC values can be limited in use for low signal-to-noise ratio images.

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Conclusion

Therefore, when quantifying colocalization, you should be guided by the type of biological problem you are trying to tackle as well as consider possible technical issues with analyzed images. Both co-occurrence and correlation measures of colocalization are capable of providing complementary information about a biological system, but should be carefully targeted for appropriate tasks.

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