The Wenner-Gren Institute, Stockholm University, 106 91 Stockholm, Sweden.
Cytometry A. 2010 Aug;77(8):733-42. doi: 10.1002/cyto.a.20896.
The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.
Pearson 相关系数 (PCC) 和 Mander 重叠系数 (MOC) 用于量化荧光团之间的共定位程度。MOC 的引入是为了克服 PCC 存在的问题。这两个系数在数学上相似，区别在于使用的是绝对强度 (MOC) 还是偏离均值 (PCC)。一系列相关数据集扩展到 PCC 的极限，仅引起了 MOC 的有限响应。PCC 不受偏移量变化的影响，而 MOC 在偏移量为正时增加。这两个系数都与增益无关。MOC 是一种混淆的混合测量方法，它将相关性与强烈的共现形式结合在一起，偏向于高强度组合，淡化了强度较低或两者都较低的组合，并忽略了空白像素。PCC 仅测量相关性。一个令人惊讶的发现是，添加第二个不相关的群体可以大大增加测量的相关性，这表明排除背景像素的重要性。总体而言，由于 MOC 对数据的实质性变化没有反应，并且难以解释，因此它既不是 PCC 的替代物，也不是有用的替代品。MOC 不适合通过相关性或共现来测量共定位。
