I'm using the exportNetworkToCytoscape function to export the module of interest to cytoscape. The tutorial first calculate TOM, select node in the network, choosing a threshold of the edge and then export to cytoscape. An edge can exists when the weight between two nodes is above the threshold.

In cytoscape, I map the degree of nodes to node size, which means that the more connection one node has, the bigger size it will be. The node with big size will be considered hub genes.But the hub genes I selected from the visualization step in cytoscape is completely different from hub genes chosen based on module membership. When I look into the source code of exportNetworkToCytoscape on github, I found it first calculate a dist measure on TOM, and then apply the threshold to the dist measure. I'm wondering if it is logic, because TOM seems to be a measurement of correlation between two nodes,and just filter the edges with low topological overlap is fine, why do we have to calculate the dist of TOM and filter edge on that measure? And why do the hub genes selected from cytoscape is completely different from module membership?

1. So the"weight" output of the edges file generated by exportNetworkToCytoscapeis based on Topological Overlap Matrix (TOM), as oppesd to pearson correlation used to calculate distance from eigengene during modules generation which can be restricted by minKMEtoStay? Is it correct?2. IS this weight (generated byexportNetworkToCytoscape)istheTopological Overlap Matrix values?Is it in in direct proportion to high correlation between genes? i.e., high weight values means high correlation, and low values mean low correlation?

3. What is the recommendedthreshold for this weight when usingexportNetworkToCytoscape?Or what would be a good way to select this threshold?

The weight generated by exportNetworkToCytoscape is exactly the matrix you give it as input. In the tutorials we use TOM but you could also use Pearson correlation or the adjacency. KME is not a measure of edge weight since KME is not a pairwise measure and hence is not used in the exportNetwork... functions.

TOM and Pearson correlation tend to be highly (Spearman-)correlated, so "relatively" high TOM implies "relatively" high correlation (here "relative" is relative to other gene pairs) but they are obviously not linearly related.

Thank you very much!Would be a good way to select the "threshold", when using

exportNetworkToCytoscape?My operational answer is to select a threshold that keeps the file size manageable, then use filtering in Cytoscape to interactively choose a threshold that results in an informative plot. This assumes that Cytoscape is only used for visualization; if you're going to use Cytoscape for further analysis, you should probably set the threshold to zero.

Thank you very much!

What further analysis can be done in Cytoscape? Selecting 0 threshold will output all possible edges. Now if we use Cytoscape-Network Analyser, the degree will all be same (= n-1). I feel only visualisation can be done in Cytoscape for weighted networks. Applying threshold and then reanalysis will make it equivalent to using hard-threshold for network construction.