Dear Amy,

I have used JaCoP during my thesis. It's a great tool. I would think, that the right threshold might depend on your images and specially the S/N ratio. I usually use wide field Z-Stacks with subsequent deconvolution and choose the threshold not by myself, but on the mathematical options ImageJ offers. I would usually recommend for example Yen or Otsu thresholds with the option stack histogram checked.

You should give different threshold methods a try - with maybe some generic sample images (you might also try to duplicate one stack as positive control 100% colocalization and deleting half of the content partial colocalization).

In the end you might see that you will end less and less restricted threshold might not influence the result any more. Getting back to the threshold approach with highest restriction already reaching the plateau of 100% colocalization can be the best choice.

I hope I explained every thing in a understandable manure?

If not, please ask?

But I would also love to here what other users recoment?!

kind regards

Soenke

for thresholds I usually move to a zone where there's nothing, and measure background intensity..then I use this as a threshold. IMHO this is rigorous enough to assure to not skew the data....

You can also try this article:

Am J Physiol Cell Physiol. 2011 Apr;300(4):C723-42. doi: 10.1152/ajpcell.00462.2010. Epub 2011 Jan 5.

A practical guide to evaluating colocalization in biological microscopy.

Dunn KW1, Kamocka MM, McDonald JH.

I found it very useful when start to work with JaCoP

Sonke and Christoph give good answers and I agree with both. There is a second approach which is nice whereby you take two identical images of the same field to essentially remove noise. It is described in Microscopy and Analysis 2008 Sept. edition, by Adler et al. They called it RBNCC. If you read it (here http://tinyurl.com/n9hq8x9 ), it's quite easy to follow and implement in ImageJ, and would be pretty easy to script too. I've never compared whether it is as good as taking a single z stack and deconvolving prior to colocalisation analysis- this is still my preferred option. Lastly, the Costes automatic background thresholding in JacOP works well in my opinion.

I am using a plan Apo 63x oil objective with an NA of 1.4. And I control for noise with a secondary only control. I have not set up a cross talk control (i.e. goat anti mouse on Rab). But I usually check that I do not have signal in the other channel in single labeled samples. I do not usually capture these images, but I can do so moving forward. I have set up neg controls for co-localization using DAPI and a cytoplasmic protein. So I will set up the 100% control as well. I have the Dunn reference and I will look into the others. Then I will explore the other thresholding options and see how that affects the analysis. Thank you so much for the input and guidance.

Read the coloc2 wiki page on the Fiji wiki to learn all about it. There is an automated method by Costes to set thresholds reproducibly. Region of interest selection, low signal noise, chromatic correction, etc all important as mentioned above.