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Created page with '#Open ImageJ Software #Prior to performing colocalisation analysis save cell images as experiment files #Open an experiment file in ImageJ by File->Open->Select File #Select Fi...'
#Open ImageJ Software
#Prior to performing colocalisation analysis save cell images as experiment files
#Open an experiment file in ImageJ by File->Open->Select File
#Select File and create composite by Image->color>create composite
#Select File and split by Image->color->Split
#Select each image and change to 8-bit greyscale by Image->type->8bit
#Assess colocalisation by Plugins->Colocalisation analysis
'''Assessment'''
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'''Rr'''
This is the Pearson’s correlation coefficient. Zero-zero pixels are not included in this calculation.
This is a popular method of quantifying correlation in many fields of research from psychology to economics. In many forms of correlation analysis the values for Pearson’s will range from 1 to -1. A value of 1 represents perfect correlation; -1 represents perfect exclusion and zero represents random localisation. However, this is not the case for images. While perfect correlation gives a value of 1, perfect exclusion does not give a value of -1. Low (close to zero) and negative values for Pearson’s correlation coefficient for fluorescent images can be difficult to interpret. However, a value close to 1 does indicate reliable colocalisation.
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'''R'''
This is Mander’s Overlap coefficient. This is easier than the Pearson’s coefficient to comprehend. It ranges between 1 and zero with 1 being high-colocalisation, zero being low. However, the number of objects in both channel of the image has to be more or less equal.
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'''Slope'''
Slope of the line represents the "red to green" ratio, as a measure of both image intensity and colocalization. Ideally, the slope should be equal to 1 (y=x), however, it is more likely that one of the immunostained colors will be darker than the other causing the slope to tend more towards that axis. Good colocalization will give a scatterplot which is best fit by a linear curve, where the slope of this curve is representative of the ratio of immunostained colors.
See following link for more information:
[http://www.uhnresearch.ca/facilities/wcif/imagej/colour_analysis.htm]
#Prior to performing colocalisation analysis save cell images as experiment files
#Open an experiment file in ImageJ by File->Open->Select File
#Select File and create composite by Image->color>create composite
#Select File and split by Image->color->Split
#Select each image and change to 8-bit greyscale by Image->type->8bit
#Assess colocalisation by Plugins->Colocalisation analysis
'''Assessment'''
----
'''Rr'''
This is the Pearson’s correlation coefficient. Zero-zero pixels are not included in this calculation.
This is a popular method of quantifying correlation in many fields of research from psychology to economics. In many forms of correlation analysis the values for Pearson’s will range from 1 to -1. A value of 1 represents perfect correlation; -1 represents perfect exclusion and zero represents random localisation. However, this is not the case for images. While perfect correlation gives a value of 1, perfect exclusion does not give a value of -1. Low (close to zero) and negative values for Pearson’s correlation coefficient for fluorescent images can be difficult to interpret. However, a value close to 1 does indicate reliable colocalisation.
----
'''R'''
This is Mander’s Overlap coefficient. This is easier than the Pearson’s coefficient to comprehend. It ranges between 1 and zero with 1 being high-colocalisation, zero being low. However, the number of objects in both channel of the image has to be more or less equal.
----
'''Slope'''
Slope of the line represents the "red to green" ratio, as a measure of both image intensity and colocalization. Ideally, the slope should be equal to 1 (y=x), however, it is more likely that one of the immunostained colors will be darker than the other causing the slope to tend more towards that axis. Good colocalization will give a scatterplot which is best fit by a linear curve, where the slope of this curve is representative of the ratio of immunostained colors.
See following link for more information:
[http://www.uhnresearch.ca/facilities/wcif/imagej/colour_analysis.htm]
