This video shows how to use Coloc2 and JACoP for colocalization studies with Fiji/ImageJ. The image shown in this video is available at cellimagelibrary.org/images/13557.
Hi Thierry, when I run coloc2, I cannot get scatter plot. There is just a line and black backgroud. Can you figure out it? Your help would be greatly appreciated. Thank you!.
Hi! It's hard to tell like this, maybe you can try on another computer. If it works then, it means that there is a problem with the installatin of Fiji on your computer, I'm not sure I would have a solution then. Good luck!
Hi. If I have a 3 Chanells (red, green and blue) and whant to calculate Pearson coefficient with JACoP? So, I should calculate red+green, red+blue, green+blue and then calculate avarage or which number (coefficient) is correct?
@Thierry Pécot Thank you for the detailed video. I am trying to study the ER-mitochondria contact sites. I have used respective tracker dyes and trying to measure colocalization by JaCoP plugin in Fiji. I am having the issue of getting similar Manders and Pearson's coefficient values for all the ROIs in an image and even without any ROI, I get the same values (I'm trying to set the same threshold value for every ROI in one image). Another issue is that the threshold is changing for every ROI in the same image when I click the plugin every time. Isn't the threshold supposed to be the same? Your help would be greatly appreciated. I am trying to figure this out for the past 3 days. Thank you!.
Hi Razia! It's not surprising to get different values across the ROIs in your images, there are always variabilities when observing biological processes. However, if you have a sufficiently high number of observations, you should be able to conclude. Then, the threshold values are used to segment your objects, it is acceptable to have different values for these thresholds depending on the intensity variations that you observe locally. You can also investigate other ways to segment your objects. For instance, it might be a good idea to normalize the intensity so you can use the same threshold. At the end of the day, as for any image analysis task, there are many ways to do it, but you need to make sure you are careful, that your analysis makes sense and is well described in the method section of the articles you write. It is a bit difficult for me to offer more help, I would suggest if it's possible to find image analysis experts around you so that you can talk about it in more details. Hope it'll help.
@@thierrypecot8747 Thank you for your reply. My problem is JaCoP plugin is not handling the ROIs. I get similar values for all the ROI. In other words, ROIs are not being selected. Is there a way I can use JaCOP on images with ROIs (all ROIs were added to ROI manager). I don't know if I'm missing something in the steps to be performed. Thanks in advance
@@raziasultana8103 Hi Razia! You're right, JaCOP does not handle ROIs, so the whole image is considered. If you want to compute the Manders coefficients in some parts of your image only, you'll have to crop your image when using JaCOP, that's the only way unfortunately. Hope it'll help.
Hi! It depends on what you want to do. Clearly, you should never consider below. If you use whole images, considering above threshold will probably help most of the time. If you compute the Pearson correlation for ROIs, you probably won't need threshold.
Hi Thierry, when I run coloc2 on raw image and background subtracted(Rolling ball radius subtraction) image and the results varies. To perform Pearson’s test is it required to do some kind of background subtraction of the image before ROI selection to remove any cellular auto fluorescence and noise? I am using Coloc2 plugin for pearson's test, do I have to convert my images to 8 bit or using 12 or 16 bit image is okay? For Manders, M1 and M2 I use JaCop. I use 12 bit image, do a background subtraction from the entire image, draw an ROI and make copy of ROI and then run Jacop on different cells/ROI from the same image. Is this a correct way? 1. How to determine the best background subtraction method? a) Process- math-subtract(the mean value from area outside cell) would remove only off cell background, right? what about on cell background? b) If I use Rolling ball background subtraction then how to determine the correct radius for 12 bit images? And is sliding paraboloid better? 2. JaCop does auto thresholding which can be manually changed, shall I rely on Jacop's auto threshold or manually change the percentage based on one of imageJ algorithm(like otsu) and then use the same algorithm for all images?
Hi! It's normal that you obtain different results when you process the Pearson correlation with and without background subtraction, as images after background subtraction are actually different. The Costes-based thresholding, based on noise statistics, is a good way to get rid of background when applying the Pearson correlation. Defining ROIs for the specific regions you're interested in measuring colocalization will help as well. With coloc2, you don't have to convert your 12-16 bits images to 8 bits images. Manders coefficients with JaCop use segmentation, background subtraction can help to identify the object localization, depending on the images. You could also apply more sophisticated segmentations if it gives you more satisfying results, but in that case, you'll have to run JaCop twice: the first time, you can use the segmentation in channel 1 and the intensity in channel 2, and the second time the intensity in channel 1 and the segmentation in channel 2, so you can obtain both coefficients. If you use the thresholding in JaCop, it might be a good idea to verify and adjust the thresholds if needed. If you know experts around you, it might be a good idea to talk about these different points with them to make sure that you do it the right way. Hope this will help!
Hi Thierry, i always get two warnings, (1) zero to zero ratio too high (2) y-intercept far from zero....Solution given is take the ROI, even after taking the ROI, it still shows the same warnings, should i ignore the it or take still small ROIs
Hi! Warnings are there mainly to make sure you think about what you do. Using ROIs is a good way to make sure you do not consider too much background (which can wrongly influence the results) or to focus on a particular region in your image. If you define a ROI that makes sense for your analysis, you shouldn't worry about the remaining warnings.
Thierry Pécot My images usually has more than cells and should i analysis the whole image et one go (may be take 8 images containing 40 cells) or each cell individual by defining the ROI, and eventually find the significance??
It's not clear what you are trying to do here. You talk about cells, but I don't know what biological objects you are interested in evaluating the colocalization. If you are interested by the colocalization between objects of interest in cells, you should use ROIs for each cell, either manually or by using automatic segmentation methods. If you are looking for colocaization between cells, you should include all cells that are evaluated. Hope it'll help.
@@thierrypecot8747 Thanks for the reply...My protein of interest is ER resident protein. I have image which usually contains more than 2 cells, so i draw the ROIs along ER (usually 16 ROIs) and then calculate the Pearsons and Manders simultaneously. Still get these warnings. Also in some ROIs i get pearson R value of 0.13 and in some regions it is 0.92, like it changes some much..
@@MrUnis Hi! It seems that you define ROIs the right way. Getting warnings is normal, they are warnings, not errors. Having different values is not surprising, generally speaking there is a lot of variability when observing biological phenomena, so you can end up with discrepancies across observations, that is why you need to observe a sufficiently large amount of data. Overall, it looks fine. It might be a good idea to talk with skilled people around you. Hope it'll help.
Hi Tatiana. I haven't heard about any approach with more than 2 channels. It would not be difficult to expand Pearson Correlation Coefficients (PCC) or Manders' Colocalization Coefficients (MCC) to any number of channels. For both approaches, you would get something interesting if all markers are spatially close , something difficult to interpret otherwise (anti-colocalization with PCC for example). That is why people generally look at colocalization with only a pair of markers, which in your case would lead to 3 separate analyses. Hope it will help.
The warnings are there to make sure you think about what you do and they are self explanatory. When you are not used to the plugin, you should go through them to be sure that you are doing the right thing. When you are used to the plugin, you'll realize that most of the time, you get the same warnings.
Thank you so much! Very helpful tutorial
Glad to see it's useful!
Hi Thierry, when I run coloc2, I cannot get scatter plot. There is just a line and black backgroud. Can you figure out it? Your help would be greatly appreciated. Thank you!.
Hi! It's hard to tell like this, maybe you can try on another computer. If it works then, it means that there is a problem with the installatin of Fiji on your computer, I'm not sure I would have a solution then. Good luck!
Hi. If I have a 3 Chanells (red, green and blue) and whant to calculate Pearson coefficient with JACoP? So, I should calculate red+green, red+blue, green+blue and then calculate avarage or which number (coefficient) is correct?
@Thierry Pécot Thank you for the detailed video. I am trying to study the ER-mitochondria contact sites. I have used respective tracker dyes and trying to measure colocalization by JaCoP plugin in Fiji. I am having the issue of getting similar Manders and Pearson's coefficient values for all the ROIs in an image and even without any ROI, I get the same values (I'm trying to set the same threshold value for every ROI in one image). Another issue is that the threshold is changing for every ROI in the same image when I click the plugin every time. Isn't the threshold supposed to be the same? Your help would be greatly appreciated. I am trying to figure this out for the past 3 days. Thank you!.
Hi Razia! It's not surprising to get different values across the ROIs in your images, there are always variabilities when observing biological processes. However, if you have a sufficiently high number of observations, you should be able to conclude. Then, the threshold values are used to segment your objects, it is acceptable to have different values for these thresholds depending on the intensity variations that you observe locally. You can also investigate other ways to segment your objects. For instance, it might be a good idea to normalize the intensity so you can use the same threshold. At the end of the day, as for any image analysis task, there are many ways to do it, but you need to make sure you are careful, that your analysis makes sense and is well described in the method section of the articles you write. It is a bit difficult for me to offer more help, I would suggest if it's possible to find image analysis experts around you so that you can talk about it in more details. Hope it'll help.
@@thierrypecot8747 Thank you for your reply. My problem is JaCoP plugin is not handling the ROIs. I get similar values for all the ROI. In other words, ROIs are not being selected. Is there a way I can use JaCOP on images with ROIs (all ROIs were added to ROI manager). I don't know if I'm missing something in the steps to be performed. Thanks in advance
@@raziasultana8103 Hi Razia! You're right, JaCOP does not handle ROIs, so the whole image is considered. If you want to compute the Manders coefficients in some parts of your image only, you'll have to crop your image when using JaCOP, that's the only way unfortunately. Hope it'll help.
@@thierrypecot8747 I got it.. Thank you so much for your prompt replies. I appreciate it
@@raziasultana8103 Glad to be helpful, good luck with your analysis!!!
When the Pearson correlation above, below or with no threshold is different which one do you use in your analysis?
Hi! It depends on what you want to do. Clearly, you should never consider below. If you use whole images, considering above threshold will probably help most of the time. If you compute the Pearson correlation for ROIs, you probably won't need threshold.
Hi Thierry, when I run coloc2 on raw image and background subtracted(Rolling ball radius subtraction) image and the results varies. To perform Pearson’s test is it required to do some kind of background subtraction of the image before ROI selection to remove any cellular auto fluorescence and noise? I am using Coloc2 plugin for pearson's test, do I have to convert my images to 8 bit or using 12 or 16 bit image is okay?
For Manders, M1 and M2 I use JaCop. I use 12 bit image, do a background subtraction from the entire image, draw an ROI and make copy of ROI and then run Jacop on different cells/ROI from the same image. Is this a correct way?
1. How to determine the best background subtraction method? a) Process- math-subtract(the mean value from area outside cell) would remove only off cell background, right? what about on cell background? b) If I use Rolling ball background subtraction then how to determine the correct radius for 12 bit images? And is sliding paraboloid better?
2. JaCop does auto thresholding which can be manually changed, shall I rely on Jacop's auto threshold or manually change the percentage based on one of imageJ algorithm(like otsu) and then use the same algorithm for all images?
Hi!
It's normal that you obtain different results when you process the Pearson correlation with and without background subtraction, as images after background subtraction are actually different. The Costes-based thresholding, based on noise statistics, is a good way to get rid of background when applying the Pearson correlation. Defining ROIs for the specific regions you're interested in measuring colocalization will help as well. With coloc2, you don't have to convert your 12-16 bits images to 8 bits images.
Manders coefficients with JaCop use segmentation, background subtraction can help to identify the object localization, depending on the images. You could also apply more sophisticated segmentations if it gives you more satisfying results, but in that case, you'll have to run JaCop twice: the first time, you can use the segmentation in channel 1 and the intensity in channel 2, and the second time the intensity in channel 1 and the segmentation in channel 2, so you can obtain both coefficients. If you use the thresholding in JaCop, it might be a good idea to verify and adjust the thresholds if needed.
If you know experts around you, it might be a good idea to talk about these different points with them to make sure that you do it the right way.
Hope this will help!
@@thierrypecot8747 does segmentation mean background subtraction or is it another processing tool in image j. Please let me know. Thank you
Hi Thierry, i always get two warnings, (1) zero to zero ratio too high (2) y-intercept far from zero....Solution given is take the ROI, even after taking the ROI, it still shows the same warnings, should i ignore the it or take still small ROIs
Hi! Warnings are there mainly to make sure you think about what you do. Using ROIs is a good way to make sure you do not consider too much background (which can wrongly influence the results) or to focus on a particular region in your image. If you define a ROI that makes sense for your analysis, you shouldn't worry about the remaining warnings.
Thierry Pécot My images usually has more than cells and should i analysis the whole image et one go (may be take 8 images containing 40 cells) or each cell individual by defining the ROI, and eventually find the significance??
It's not clear what you are trying to do here. You talk about cells, but I don't know what biological objects you are interested in evaluating the colocalization. If you are interested by the colocalization between objects of interest in cells, you should use ROIs for each cell, either manually or by using automatic segmentation methods. If you are looking for colocaization between cells, you should include all cells that are evaluated. Hope it'll help.
@@thierrypecot8747 Thanks for the reply...My protein of interest is ER resident protein. I have image which usually contains more than 2 cells, so i draw the ROIs along ER (usually 16 ROIs) and then calculate the Pearsons and Manders simultaneously. Still get these warnings. Also in some ROIs i get pearson R value of 0.13 and in some regions it is 0.92, like it changes some much..
@@MrUnis Hi! It seems that you define ROIs the right way. Getting warnings is normal, they are warnings, not errors. Having different values is not surprising, generally speaking there is a lot of variability when observing biological phenomena, so you can end up with discrepancies across observations, that is why you need to observe a sufficiently large amount of data. Overall, it looks fine. It might be a good idea to talk with skilled people around you. Hope it'll help.
@@thierrypecot8747 thanks for the video and replying back, it really helped.....thank you
@@MrUnis You're very welcome!
Is it possible to analyze colocalization between 3 channels? For example, the overlap between red/green/blue channels
Hi Tatiana. I haven't heard about any approach with more than 2 channels. It would not be difficult to expand Pearson Correlation Coefficients (PCC) or Manders' Colocalization Coefficients (MCC) to any number of channels. For both approaches, you would get something interesting if all markers are spatially close , something difficult to interpret otherwise (anti-colocalization with PCC for example). That is why people generally look at colocalization with only a pair of markers, which in your case would lead to 3 separate analyses. Hope it will help.
Yes try EzColocalization plug-in
what about the generated warnings ??
The warnings are there to make sure you think about what you do and they are self explanatory. When you are not used to the plugin, you should go through them to be sure that you are doing the right thing. When you are used to the plugin, you'll realize that most of the time, you get the same warnings.