Puncta counting

Sample image and/or code

Control.ome.tif (3.0 MB)
Test.ome.tif (3.0 MB)

I want to calculate the puncta’s within the given control and test image and further want to quantitate them. Can anyone please help me for that.
I tried
Primari object identification but still not able to quantitate it. can someone please tell me how to design pipeline for my problem. I also want to reduce the background am getting in control image. I want to quantify puncta’s in control and i want to draw a graph out of that. (I tried CellProfiler.ink latest version)

Thank you in anticipation

What software packages and/or plugins have you tried?

Could you upload the pipeline you’ve tried so far?

Hi Nikhil,

You may also want to check out the Speckle Counting example at Examples | CellProfiler ; it does basically what you want (finds and counts small puncta), so it should be a good place to build from.

Hello Beth
Thank you for your kind reply
Beth, I actually tried Speckle counting pipeline but it is not working in my case. I want to simply count the punctas and want an output files which will give me actual number so i can quantitate the difference between control and test
Thank You

Hi David
Thank you for your reply
Here am attaching the file pipeline which I tried for counting Punctas
PLA processed.cpproj (619.7 KB)

Hi @nikhil358,

I took a look at your pipeline and I have a few suggestions that I think will help. I’d also recommend working through our tutorials on YouTube, such as this workshop - while the problem is different, it will help you learn principles of how CellProfiler works: CellProfiler Workshop - YouTube

If I understand your data correctly, the Test and Control images are two different images that each contain the same channels. I think you may need to change how you import these images into CellProfiler in order to set up your experiment correctly.

In the NamesAndTypes module, you are configuring an “ImageSet” to contain both a Test and a Control image. Essentially, you’re telling CellProfiler that the Test image and the Control image were acquired at the same imaging position/site. I’d recommend using the “All images” mode instead.

Since your images are RGB, I’d also recommend importing them in “Color” mode and then using the module “ColorToGray” to split the individual channels to separate images that can be processed individually in CellProfiler.

More information on configuring images for analysis is available in our help, available by clicking on the ? buttons in CellProfiler or online here:
https://cellprofiler-manual.s3.amazonaws.com/CellProfiler-4.1.3/help/projects_configure_images.html

Once you’ve imported your images, a rough outline of what you’ll probably want to try to do is:

  • segment Nuclei w/ IdentifyPrimaryObjects as objects using the Blue channel
  • EnhanceOrSuppressFeatures w/ the Red channel
  • segment Speckles w/ IdentifyPrimaryObjects w/ the Red channel
  • relate the Nuclei (parents) to the Speckles (children). Be sure that each of these objects have unique names
  • make desired measurements
  • ExportToSpreadsheet

You’ll run the same pipeline on both test and control images. The output Image.csv file will have a Count_Speckles (or whatever you named your Speckle objects in IdentifyPrimaryObjects) column that contains the # of speckles per image. The Nuclei.csv file will have a Children_Speckles_Count column with the number of Speckles per Nuclei object.

I hope this is helpful! Let us know how it goes.
Cheers,
Pearl

Dear Pearl
Thank you so much for your reply
I will surely try the processing the way to told
And will reach you i find any difficulty.