counting of colocation area

[agus wijoyo]

Dear Forum

I would like to find out the location of my protein in the cells, the protein was stained with Red Fluorescent Protein, and located in both the cytoplasm and nucleus. The nucleus of the cells was stained with DAPI (blue colour). After merge the 2 image, there were part of protein which was located in the nucleus, and make colocation with the blue colour of the nucleus. I want to count the percentage of the protein in the nucleus area and in the cytoplasm. Please give me an advise

 

Thank you

Gus
 




      ________________________________________________________
Bergabunglah dengan orang-orang yang berwawasan, di di bidang Anda! Kunjungi Yahoo! Answers saat ini juga di http://id.answers.yahoo.com/

[Daniel James White]

Dear Gus,

Using a 2 colour merge to look for "co-location" of proteins is a
poor mans way of doing it.
This simple way is very prone to error as it is totally subjective:
The amount of overlap you see depends on the relative brightness of  
the 2 colour channel/images.
Some people are colour blind and cant see the results (for red and  
green especially).
Green looks brighter than red, which looks brighter than blue,
so your brain and eyes have a hard time seeing what is really going  
on, especially for lower intensities overlapping.
There are no statistical tests involved to determine if what you see  
is random or real,
so what you see in a single image could be misleading.

Remember the colours are false anyway, DAPI isnt 100% blue, and RFP  
isnt 100% red,
so it is in many ways silly to represent them in a black to single  
colour R G or B
Better to use a grey scale or spectrum look up table which our eyes  
can see better.


Search this list for threads on colocalisation / colocalization
and there is lots of discussion on how to do it objectively and  
quantitatively.

In short,
use the methods of Manders and Costes
which are in the colocalisation plugins for imageJ

This gives you:
1) Manders coefficients - which describe the proportion of one color  
colocalised with the other, and vice versa.
        These are insensitive to differences in the intensity between colour  
channels, and so robust between different images of the same sample  
and possibly even different samples.
2) a way to set the thresholds (what is real signal and what is  
background) in a reliable objective  and reproducible way (Costes)
3) A statistical test to see if the colocalisation is random or real.
4) A 2D histogram, where you can much better see correlation in  
spatial intensity distribution than in a 2 colour merge image.
5) A map of the colocalised pixels to compare with the original images.

Images must be correctly spatially sampled, according to Nyqvist  
theorem (about 80-100 nm in xy and about 250 nm in z for a 1.4 NA  
objective, so you don't miss some of the information the microscope  
could see).

Fluorescent beads should be used as positive controls (try tetraspek  
from invitrogen),
so you can see if the different colours appear in the same place.  
(even if you use apochromat objectives , they might not be,
and you may need to precisely align your scanners/microscopes optics,  
or even correct the images in post processing. Objects at the edges of  
a large field of view suffer badly from chromatic aberration quite  
often)


I strongly believe that pixel intensity based colocaisation analysis  
results should:

1) show both colour channels images using a spectrum look up table  
(not black to red / blue /green  - the dyes are not 100% R G or B  
anyway)
2) show the thresholds used   (as calculated by the Costes method)
3) Show the thresholded Manders coefficients,
4) show the statistical significance according to Costes, Fay or van  
Steensel)
5) show the 2D histogram (which is very informative)
6) be done in 3D in a 3D sample (else you miss much important  
information)
7) could show a colour merge image (i really dont like those though) -  
but better a colocalisation map


The same methods are also implemented in BioImageXD, and it should be  
faster (also free software)
Imaris also has the same maths - nearly. Imaris is nice, but expensive.

You can also do object based colocalisation, but thats another story,  
involving segemtning objects out of the images. ...

I will send you the pdf files for Manders and Costes off list  (anyone  
else want them... Manders is hard to find)
Read, digest, understand, become enlightened. The concepts are quite  
simple, don't be scared off by the equations.

cheers

Dan



On Apr 29, 2008, at 6:00 AM, IMAGEJ automatic digest system wrote:

> Date:    Mon, 28 Apr 2008 02:05:54 -0700
> From:    agus wijoyo <[hidden email]>
> Subject: counting of colocation area
>
> Dear Forum
>
> I would like to find out the location of my protein in the cells,  
> the prote=
> in was stained with Red Fluorescent Protein, and located in both the  
> cytopl=
> asm and nucleus. The nucleus of the cells was stained with DAPI  
> (blue colou=
> r). After merge the 2 image, there were part of protein which was  
> located i=
> n the nucleus, and make colocation with the blue colour of the  
> nucleus. I w=
> ant to count the percentage of the protein in the nucleus area and  
> in the c=
> ytoplasm. Please give me an advise
>
> =20
>
> Thank you=20
>
> Gus
> =20

Dr. Daniel James White BSc. (Hons.) PhD
Senior Microscopist / Image Processing and Analysis
Light Microscopy Facility
Max Planck Institute of Molecular Cell Biology and Genetics
Pfotenhauerstrasse 108
01307 DRESDEN
Germany


New Mobile Number!!!

[phone] (German Mobile)
+49  (0)351 210 2627 (Work phone at MPI-CBG)
+49  (0)351 210 1078 (Fax MPI-CBG LMF)

http://www.bioimagexd.net
http://www.chalkie.org.uk
[hidden email]
( [hidden email] )

[agus wijoyo]

Dear Mr Dan

Thank you for your explanation, I will try your suggestion. I am looking forward of Manders and Costes off list from you. I will learn these since I am new in image analysis.

Best Regards
Gus





      ________________________________________________________
Bergabunglah dengan orang-orang yang berwawasan, di di bidang Anda! Kunjungi Yahoo! Answers saat ini juga di http://id.answers.yahoo.com/

[Daniel James White]

Hi All,

Due to popular demand (cough...)
here are the links to the colocalisation analysis course material
we are planning to teach here at MPI-CBG / BioZ / MTZ / CRTD  in  
Dresden, Germany,
and have test driven on a course at the University of Jyvaskyla,  
Finland already.

Look at the image processing section at:

http://tu-dresden.de/die_tu_dresden/fakultaeten/medizinische_fakultaet/mtz/mtzImaging/ifn/teaching_material

apologies for the long url

feedback / comments / criticism / objections / abuse / etc. welcome

Further, there is all kinds of fab stuff to be seen at that page
including PDFs and videos from our microscopy courses
(special thanks to Peter Evennett and Michael Weber and the IFN team)

Dan White


Begin forwarded message:

> From: Dan White <[hidden email]>
> Date: April 29, 2008 12:21:59 PM GMT+02:00
> To: ImageJ Interest Group <[hidden email]>
> Cc: [hidden email]
> Subject: Re: counting of colocation area
>
> Dear Gus,
>
> Using a 2 colour merge to look for "co-location" of proteins is a
> poor mans way of doing it.
> This simple way is very prone to error as it is totally subjective:
> The amount of overlap you see depends on the relative brightness of  
> the 2 colour channel/images.
> Some people are colour blind and cant see the results (for red and  
> green especially).
> Green looks brighter than red, which looks brighter than blue,
> so your brain and eyes have a hard time seeing what is really going  
> on, especially for lower intensities overlapping.
> There are no statistical tests involved to determine if what you see  
> is random or real,
> so what you see in a single image could be misleading.
>
> Remember the colours are false anyway, DAPI isnt 100% blue, and RFP  
> isnt 100% red,
> so it is in many ways silly to represent them in a black to single  
> colour R G or B
> Better to use a grey scale or spectrum look up table which our eyes  
> can see better.
>
>
> Search this list for threads on colocalisation / colocalization
> and there is lots of discussion on how to do it objectively and  
> quantitatively.
>
> In short,
> use the methods of Manders and Costes
> which are in the colocalisation plugins for imageJ
>
> This gives you:
> 1) Manders coefficients - which describe the proportion of one color  
> colocalised with the other, and vice versa.
> These are insensitive to differences in the intensity between  
> colour channels, and so robust between different images of the same  
> sample and possibly even different samples.
> 2) a way to set the thresholds (what is real signal and what is  
> background) in a reliable objective  and reproducible way (Costes)
> 3) A statistical test to see if the colocalisation is random or real.
> 4) A 2D histogram, where you can much better see correlation in  
> spatial intensity distribution than in a 2 colour merge image.
> 5) A map of the colocalised pixels to compare with the original  
> images.
>
> Images must be correctly spatially sampled, according to Nyqvist  
> theorem (about 80-100 nm in xy and about 250 nm in z for a 1.4 NA  
> objective, so you don't miss some of the information the microscope  
> could see).
>
> Fluorescent beads should be used as positive controls (try tetraspek  
> from invitrogen),
> so you can see if the different colours appear in the same place.  
> (even if you use apochromat objectives , they might not be,
> and you may need to precisely align your scanners/microscopes  
> optics, or even correct the images in post processing. Objects at  
> the edges of a large field of view suffer badly from chromatic  
> aberration quite often)
>
>
> I strongly believe that pixel intensity based colocaisation analysis  
> results should:
>
> 1) show both colour channels images using a spectrum look up table  
> (not black to red / blue /green  - the dyes are not 100% R G or B  
> anyway)
> 2) show the thresholds used   (as calculated by the Costes method)
> 3) Show the thresholded Manders coefficients,
> 4) show the statistical significance according to Costes, Fay or van  
> Steensel)
> 5) show the 2D histogram (which is very informative)
> 6) be done in 3D in a 3D sample (else you miss much important  
> information)
> 7) could show a colour merge image (i really dont like those though)  
> - but better a colocalisation map
>
>
> The same methods are also implemented in BioImageXD, and it should  
> be faster (also free software)
> Imaris also has the same maths - nearly. Imaris is nice, but  
> expensive.
>
> You can also do object based colocalisation, but thats another  
> story, involving segemtning objects out of the images. ...
>
> I will send you the pdf files for Manders and Costes off list  
> (anyone else want them... Manders is hard to find)
> Read, digest, understand, become enlightened. The concepts are quite  
> simple, don't be scared off by the equations.
>
> cheers
>
> Dan
>
>
>
> On Apr 29, 2008, at 6:00 AM, IMAGEJ automatic digest system wrote:
>
>> Date:    Mon, 28 Apr 2008 02:05:54 -0700
>> From:    agus wijoyo <[hidden email]>
>> Subject: counting of colocation area
>>
>> Dear Forum
>>
>> I would like to find out the location of my protein in the cells,  
>> the prote=
>> in was stained with Red Fluorescent Protein, and located in both  
>> the cytopl=
>> asm and nucleus. The nucleus of the cells was stained with DAPI  
>> (blue colou=
>> r). After merge the 2 image, there were part of protein which was  
>> located i=
>> n the nucleus, and make colocation with the blue colour of the  
>> nucleus. I w=
>> ant to count the percentage of the protein in the nucleus area and  
>> in the c=
>> ytoplasm. Please give me an advise
>>
>> =20
>>
>> Thank you=20
>>
>> Gus
>> =20
>
> Dr. Daniel James White BSc. (Hons.) PhD
> Senior Microscopist / Image Processing and Analysis
> Light Microscopy Facility
> Max Planck Institute of Molecular Cell Biology and Genetics
> Pfotenhauerstrasse 108
> 01307 DRESDEN
> Germany
>
>
> New Mobile Number!!!
>
> [phone] (German Mobile)
> +49  (0)351 210 2627 (Work phone at MPI-CBG)
> +49  (0)351 210 1078 (Fax MPI-CBG LMF)
>
> http://www.bioimagexd.net
> http://www.chalkie.org.uk
> [hidden email]
> ( [hidden email] )
>
>
>
>
>

Dr. Daniel James White BSc. (Hons.) PhD
Senior Microscopist / Image Processing and Analysis
Light Microscopy Facility
Max Planck Institute of Molecular Cell Biology and Genetics
Pfotenhauerstrasse 108
01307 DRESDEN
Germany


New Mobile Number!!!

[phone] (German Mobile)
+49  (0)351 210 2627 (Work phone at MPI-CBG)
+49  (0)351 210 1078 (Fax MPI-CBG LMF)

http://www.bioimagexd.net
http://www.chalkie.org.uk
[hidden email]
( [hidden email] )

[agus wijoyo]

Dear Mr Dan

Thank you very much for the links

Regards
Gus




      ________________________________________________________
Bergabunglah dengan orang-orang yang berwawasan, di di bidang Anda! Kunjungi Yahoo! Answers saat ini juga di http://id.answers.yahoo.com/