419

edits
# Changes

→Pixel intensity spatial correlation analysis: add clarity and a little detail and link to alder2010 refuting the overlap coefficient

==== Pixel intensity spatial correlation analysis ====

These coefficients measure the ~~significance ~~amount or degree of ~~true ~~colocalization, or rather correlation and co-occurrence respectively (but should not be expressed as % values, because that is not how they are defined). ~~The ~~But if there is nothing to compare them to, what do they mean? A statistical significance test ~~is ~~was derived by Costses to evaluate the probability that the measured value of Pearson's correlation, r ~~from ~~between the two ~~colors ~~colour channels is significantly greater than values of r that would be calculated if there was only random overlapof 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 Manders' coefficient we measure are better than pure chance or not.

Other coefficients include ranked correlations such as Spearman and Kendal's Tau, %overlap of intensities or area (volume).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 be not very useful compare to Pearson's r and Mander split coefficients. Other methods include ICCS (image cross correlation spectroscopy) and a derivative of that called PPI (protein proximity index. Maybe someone wants to add PPI to the Coloc_2 plugin? [[Media:Wu2010-crosscorrelationPPI_Coloc.pdf|original article here]]

==== Object-based overlap analysis ====