This may be a silly question with an obvious answer, but here goes:
I have noticed that when I take my microarray dataset and parse it into smaller chunks (fewer probes/genes per chunk) there is a pattern that appears in my soft fit curve when performing WGCNA. Specifically I get a drop off in the scale independence curve. Instead of plateauing at around .8 or .9, the curve seems to plateau then plunges at some higher soft thresholding power.
Could anyone explain to me whats going on?
Also, is this a sign of something problematic in the data or is this a known phenomenon that occurs whenever you are working with few probes/genes. I notice this happening any time I drop the number of probes below say 2500 or thereabouts. I have looked around but really haven't found a good explanation of this anywhere thus far.
Thanks!
The fact that the curve reach a plateau an then plunges at higher powers is caused by a drastric drop in the connectivity. This is quite common when you randomly subsample your dataset as the majority of your genes are supposed to have very low connectivity while only few are highly conencted (hub). This is a fundamental aspect of 'scale free' networks.