We frequently analyze our gene expression data using WGCNA to identify modules of gene co-expression profiles. However, in generating our original dendrograms we obtain blocks that have unique characteristics.
Some blocks have higher level branches (see block 1, below):
Whereas other blocks from the same data set are more deeply branched (see block 2, below):
In performing subsequent deep splitting, and tree re-cutting, a detectCutHeight is selected (usually 0.99) that is utilized across all blocks. My question is: would it be prudent to select different detectCutHeights for individual blocks in order to isolate apparently unique branches?
Below is a modified example of block 2, wherein if a detectCutHeight of 0.9 was selected (blue dashed line), rather than the standard 0.99, two modules would be identified (red ovals), as opposed to a single larger turquoise module.
We understand the inherent problems that may arise from this approach. We've discovered that some modules identified in the cutting process, have the same color names spanning multiple blocks. Also, that selecting deeper cut heights would result in loss of some other branch information. Any guidance or experience in this matter is greatly appreciated.