Using DESeq2 I would like to obtain a heatmap of sample-to-sample distances using the rlog-transformed values. However, I'm not sure if I should use the "Euclidian" distance or the "Poisson" distance (both are suggested here). I have obtained both graphs but don't know which one I should "trust". While I think I understand the "Euclidian" approach I'm not sure to get the advantages of the "Poisson" approach. I've tried reading the fundament paper (Witten 2011) but got lost at some point B-)

Could someone:

1. illustrate a simple sample case where both methods would give **the same result**?

2. illustrate a simple sample case where both methods would give **different results**?

3. explain the advantages and drawbacks of both methods?

Many thanks!

PS: Since this might concern Bioinformatics in general, I also posted this question on Biostars and got an answer.