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Colocalization Analysis

64 bytes added, 02:42, 31 July 2015
Pixel intensity spatial correlation analysis
These coefficients measure the amount or degree of colocalization, or rather correlation and co-occurrence respectively (but should not be expressed as % values, because that is not how they are defined). But if there is nothing to compare them to, what do they mean? A statistical significance test was derived by Costses to evaluate the probability that the measured value of Pearson's correlation, r between the two colour channels is significantly greater than values of r that would be calculated if there was only random overlap of the same information. This test is performed by randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel's intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. You can get more details in [[Media:Costes etalColoc.pdf|Costes et al.]] The result of this tests tell us if the Pearsons r and split Manders' coefficients we measure are better than pure chance or not.
Other coefficients include ranked correlations such as Spearman and Kendal's Tau, Li's ICQ and the %overlap of intensities or area (volume) above one or both thresholds (coming soon to Coloc_2).
Some others are described in the literature that have been used in publications, but that have been refuted as insensetive, such as the overalp coefficient from the Manders paper, which [[Media:Adler_et_al-2010-Cytometry_Part_A.pdf|J. Adler et al.]] showed to have large problems in interpretation compared to Pearson's r and Manders' split coefficients.