3 replies to this topic

[Hugo]

Dear all

Recently a doubt was raised in how to analyze facs data.

In this specific assay we stain cells for a specific antibody and of course also the isotype to correct for it.

We treat cells with different compounds and then analyze the percentage of positive cells and the mean/median of expression.

For that we set the quadrants in the isotype and then apply the same quadrant for the corresponding condition. the percentage of positive cells in a certain condition is subtracted by the percentage of positive cells of the isotype. Until here no problems.

The question is then how to compare different conditions...

for example if we have:

control
control isotype
compound 1
compound 1 isotype
compound 2
compound 2 isotype

Do you set the quadrants to the control isotype and apply the same to all conditions, or should i set independent quadrants for each (coumpound + iso combination)

the question was raised because treatment with these compounds changed significantly the percentage of positive cells in the isotype.

hope i was clear in the question


looking forward to hear from you

Cheers

hugo

[CellSpecific.com]

Exposure to compound resulted in non-specific binding of isotype antibody to more cells. You definitely should compare your primary antibody to isotype control data. This is a classic example of why it is so important to use isotype controls.

Was there a difference between primary antibody vs. isotype control?

[Hugo]

CellSpecific.com, on Oct 14 2009, 08:01 AM, said:

Exposure to compound resulted in non-specific binding of isotype antibody to more cells. You definitely should compare your primary antibody to isotype control data. This is a classic example of why it is so important to use isotype controls.

Was there a difference between primary antibody vs. isotype control?

Hi

Indeed thats crucial to do a proper analysis. And yes there was a difference between the primary antibody vs. isotype depending on the conditions use.

But my question is really about using the same quadrants in all the situations or establishing new quadrants per condition/isotype.

Thats what i am not sure what is better.

[CellSpecific.com]

I would adjust/compare with the data represented by your best control and I believe this is the compound/isotype data. Alternatively, you can present the data using all available comparisons (show it all) e.g., data1: [untreated vs compound treated] data2: [compound treated vs. compound treated/isotype] data:3 [compound treated/isotype vs. compound treated/primary]. Line them up neatly so that it is easy for the evaluator to compare across. Good luck to you.