Colocalization analysis of cells - What's the best way? (ImageJ, Photoshop?)

Hi all,

I want to do some colocalization analysis in the spinal cord. I’ve done a combo of immunohistochemistry and in situ hybridazation and I have four colors:

DAPI = Blue
White = Gene 1
Red = Gene 2
Green = GFP transgene

I want to quantitate the co-occurrence of these signals, so for example (GFP+/Gene1+/Gene2-) etc in an efficient manner. I’ve used Photoshop in the past and used the selection too. But I know ImageJ must have a good way to do this. I’ve shied away from ImageJ in the past because I found it buggy and slow, but I’m willing to use it if it can do what I want. Are there any specific tutorials on how to do? I’m looking around, but the documentation for ImageJ is pretty verbose.


Here’s an example of what I’m looking at.

@tberta @fmoehring @Ale @zhzhj131421 @LegakisL @tonellor @mwc19 @lfqueme @YawarJQ


I have used JACop, it’s a colocalisation plug in for ImageJ/FIJI.

Download here:

Paper reference:;jsessionid=3CEBCC024702EE60161738FDF41BBB97.f02t02?v=1&t=iz72kb28&s=049cabd7894c209ed3cd15a3168f6ffe46478370

I have done integrated density using thus plug in. Although, I think it only allows to do two channels at the time.

I hope it helps!

1 Like

Thanks Marta! I’ll give it a try.

CellProfiler recently came on my radar for cell counting. It looks very powerful.

I recently saw a paper describe using CellProfiler for automated counting of DRGs

Hopefully we can come up with a reproducible pipeline that works. This would be a huge time saver.