Normalize across trials using controls

[#1]

I have a datasets of populations with a response. I triplicated the experiment, so I have 3 trials of data, but the response rate likely varies between trials. It is a hypoxia response rate, which is sensitive to things like humidity/temperature that I can't perfectly control. 

Each trial consists of a population with different treatments, plus empty vector controls. 

So like this, but with like 50 entries for each treatment/control per trial:

Trial                             Response

1 TreatmentX               999

1 Control                        576

2 TreatmentX               1111

2 Control                        700

3 TreatmentX              700

3 Control                        350

So for this example the treatment is always above control, but control varies alot. I was thinking of using Dunnetts test to see which treatments are different from control, but I want to normalize the data to account for the trial day differences. The population sizes vary so I can't just use the total average for each day, but I should be able to use my controls to normalize each trial. How do I do this in JMP?

[#2]

If it's just about calculating the ratio (or difference) per trial , you  can use the Normalization AddIn from https://marketplace.jmp.com/appdetails/Normalization+GUI 

e.g. with the settings:

- column to normalize : Response

- function: ratio or difference

- grouping: by trial

- subset: Control

[The default aggregation is median, which works well even with just a single control and is much faster than the other modes.]