I am new to WGCNA. The selection of my soft thresholding value is confusing me. My code is identical to the online tutorials except that I chose to do a signed network. These are the resulting plots

I am not sure why the y axis in the first is negative. My understanding is that a soft thresholding value should be one at which the index curve reaches a relative high value (>0.8). Any advice would be greatly appreciated.

I am not sure why the image isn't showing up. The scale free fit is essentially all negative and plateaus close to 0 after a soft thresholding value of about 18 or 19.

The negative "signed R^2" is negative when your network has more genes with high connectivity than ones with low connectivity (i.e., the regression line for the fit log(n(k))~log(k) has a positive slope). It means your network shows a topology in some ways opposite (more high connectivity than low connectivity genes) to what is normally expected (a lot of low-connetivity gens and fewer high connectivity genes).

Usually, a lot of high-connectivity genes means there is a strong global driver (e.g., you have samples from different tissues or a strong batch effect). Make sure your sample tree doesn't show very strong branches. Also, see WGCNA FAQ (https://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/faq.html) for some comments about heterogeneous data sets and lack of SFT.

Thanks. My samples were from a 16S library and it was abundance data. The section on RNA-seq data helped a lot. I basically had too many OTUs with zero reads in a majority of the samples. After I cut down on the number of OTUs and took the log of the abundance it worked just like in the tutorial.