[Bernd Jagla]

Sorry for writing in English, you can answer in French if that is more comfortable

Hi,
 
hope this finds you well.
 
I am interested in discussing transformations for cytometry data analysis.
 
Specifically, I found that mainly for reproducibility reasons, one should use the arcsinh transformation and adjust the cofactor such that there is only one population around zero.
 
Question: why not shift all values to being >=1 and then use either log transform or arcsinh, but this time adjust the cofactor to optimize the separation of different clusters?
 
I believe that one could be worried about shifting the means/MFIs of the individual populations, and this might be important for comparing between samples. But in my experience, comparing between samples is not possible without a proper alignment of the distributions. 
Some biologists say that that shift in distributions/population/MFIs is biologically significant, and I would agree. But these are different questions. Counting/identifying cell types and shifts in MFIs are different questions and should be handled separately (mho).
 
I have already spoken to a few people about this but without a clear and convincing answer.
 
Would anyone be willing to discuss this? 
If this interests many people, we might organize an afternoon to discuss it???
 
Looking forward to your answers.
 
Best,
 
Bernd