Hello all,
first of all thanks for this amazing support forum!
I would like to clarify some questions arising when analysing standard Metaphlan output (relative proportions from 0100, taxonomy table reduced to 1 common level) with Maaslin2:

I have a typcial distribition of microbiome data, i. e. lots of zeros for a given feature. So I would reckon a nonLM analysis like ZINB would be appropriate. However, when running ZINB I do not find any significant taxa whereas with default LM analysis, I have 54 significant taxa. So is normal LM analysis superior to ZINB in this case?

This brings me to my next question: How to transform the data? Log and LOGIT transformation seems to result in the highest number of significant taxa, but this may be overfitted?
In particular, I ran the following analysis model/transformation combinations and got these numbers of significant associations (all other settings left to default):
LM
Log: 54
None: 1
AST: 0
LOGIT: 92
ZINB
Log: 0
NEGBIN
NONE: 4
CPLM
NONE: 16
AST: 5
LOG: 0
LOGIT: 0
Thank you,
Philipp