I have a problem as follows show:
Weighted gene co-expression network analysis (WGCNA) was used to generate a co-occurrence modules based on the species log10-transformed abundance data, The eigen-species, which was defined as the first principle component of a module,representing the modules abundance level.so how should I deal with the modules abundance data before I run Maaslin?should I set transform=“NONE”,normalization = “NONE”,min_abundance=-1(as min value of my WGCNA output modules abundance is -0.5)?thanks.
Hi @annabi1993 - given that you have both positive and negative values in your dataset, these options make sense except that you can also set
min_abundance = -Inf if you don’t want to filter out features or provide filtered data as input (e.g. by applying filtering outside of MaAsLin 2). Hope this helps!
should I set transform=“None” ,normalization=“NONE” as my value is WGCNA output which run based on log10-transformed abundance data?
I think that makes sense.