On the pixel selection criterion for the calculation of the Pearson's correlation coefficient in fluorescence microscopy

被引:0
|
作者
Lopez, Sergio G. [1 ,2 ]
Samwald, Sebastian [1 ]
Jones, Sally [1 ]
Faulkner, Christine [1 ,2 ]
机构
[1] John Innes Ctr, Cell & Dev Biol, Norwich Res Pk, Norwich, England
[2] John Innes Ctr, Cell & Dev Biol, Norwich Res Pk, Norwich NR4 7UH, England
基金
欧洲研究理事会; 英国生物技术与生命科学研究理事会;
关键词
biomolecule interactions; colocalisation; fluorescence; microscopy; Pearson's correlation coefficient; COLOCALIZATION;
D O I
10.1111/jmi.13273
中图分类号
TH742 [显微镜];
学科分类号
摘要
Colocalisation microscopy analysis provides an intuitive and straightforward way of determining if two biomolecules occupy the same diffraction-limited volume. A popular colocalisation coefficient, the Pearson's correlation coefficient (PCC), can be calculated using different pixel selection criteria: PCCALL includes all image pixels, PCCOR only pixels exceeding the intensity thresholds for either one of the detection channels, and PCCAND only pixels exceeding the intensity thresholds for both detection channels. Our results show that PCCALL depends on the foreground to background ratio, producing values influenced by factors unrelated to biomolecular association. PCCAND focuses on areas with the highest intensities in both channels, which allows it to detect low levels of colocalisation, but makes it inappropriate for evaluating spatial cooccurrence between the signals. PCCOR produces values influenced both by signal proportionality and spatial cooccurrence but can sometimes overemphasise the lack of the latter. Overall, PCCAND excels at detecting low levels of colocalisation, PCCOR provides a balanced quantification of signal proportionality and spatial coincidence, and PCCALL risks misinterpretation yet avoids segmentation challenges. Awareness of their distinct properties should inform their appropriate application with the aim of accurately representing the underlying biology.
引用
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页数:12
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