JacoP Documentation - Object based colocalization alternatives to JacoP

Hi all,
I have a very silly problem but I am not able to find JacoP’s documentation anywhere (seems the linked died). Is it because it’s old and has been replaced by a newer plugin ? I want to do object based colocalization analysis in 3D stacks, I don’t know any alternatives other than the JacoP plugin, but without the documentation I have difficulties understanding what the output means and what it takes into account.

Thank you in advance for any piece of information !
Best
Cécile

Hi @CecileBrid,

I strongly recommend this very recent article:

It was co-written by @Fabrice_Cordelieres, who is also the original co-author of Jacop.

Furthermore, you can refer to the original article:

And to the website of Jacob:
https://imagej.nih.gov/ij/plugins/track/jacop2.html

If there is still something unclear, feel free to provide some example images and tell us what exactly you want to do.

Let us know if this helps.

Cheers,
Robert

Thank you very much for your quick and very complete answer Robert !
Unfortunately I have been through these documents and did not find what I was looking for (maybe my fault) - though it did convince me that I needed an object-based colocalization method.
Both articles explain the principles of the different colocalization techniques available but what I would need is JacoP’s documentation about its object-based functions (the link you provided only describes all correlation-based colocalization methods).
Here is my problem : at the bottom is one slice of the stack I am working on. Red clusters are cells and in yellow is a nuclear marker of cell proliferation. I treated and segmented both channels to obtain what you can see here. Now I would like to get the number of red cells that have a yellow cluster inside. I thought distance-based colocalization would answer that question but I don’t understand the output.
When I run the JacoP function I get this result:
“Distance based colocalization:
% of positive A thresholded pixels=10
% of positive B thresholded pixels=38”
So I get an info on the % of pixels of one channel that colocalize with the other channel. So it seems I get an info on pixels rather than objects which was to me the point of this method. I am quite lost.


Thanks in advance if you have any recommendation/explanation !
Best,
Cécile

Hi,

I have been running JACoP 2 on your screen capture, and here is the output:


Image A: Nuclei

Image B: Cells

Colocalization based on centres of mass-particles coincidence

Threshold for Image A=128; Image B=128

Particles size between 0 & 2391688

Image A: 10 centre(s) colocalizing out of 80

Image B: 8 centre(s) colocalizing out of 17


To do that, I’ve been using the “Centre-particles coincidence” option. The rational is that you have big objects on one channel and small one in the other one: you may want to summarize the small ones as points and see if they match with any of the underlying objects.

JACoP will compute where the centres are on image 1, and where the objects are on the image 2. It will then count the numbers of centres from image 1 falling onto objects from image 2.

From the exported data, you may see that you have 17 cells and 80 spots of nuclear marker.

When looking at the nuclei centres falling onto cells, you find 10 of them (out for 80) on cells and 8 (out of 17) centres of cells falling onto nuclear markers.

I hope this helps.

I’ve enclosed the latest version of JACoP (75.8 KB): it seems the Tudor website where it has long been hosted is down. I’ll put it on GitHub ASAP (I need to do a bit of cleanup on the user interface before).

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Hi Fabrice,
Thank you very much ! Indeed the website is down so that I had an old version of the plugin apparently - and no documentation.
The interface is much more complete and clear, and the “centre-particles coincidence” option seems to be well adapted to my needs.
Thank you once again for this beautiful work !
Best,
Cécile

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