Skewed Betweenness Centrality values resulting in almost unusable PPI networks for my university project - what can I do?


For context, I have inputted lists of proteins into STRING, which I then imported to Cytoscape, changed the size of the nodes to correlate with their degree and used continuous mapping to depict the BC values using a colour gradient. I have run into a couple of issues:

1) The highest BC value in one of my datasets is 1.0, with the second-highest around 0.7 and then the other dozens/100's of proteins incrementally decreasing as you move down the list. If I use continuous mapping and depict the BC values by a colour gradient, then the highest BC value will skew it and all my proteins will be one block colour, rather than a gradient. I am confused about how to interpret that.

2) Additionally, for some of my datasets I have increased the confidence threshold on STRING to 0.9, so when I have imported it into Cytoscape then there is a big main network, a couple of smaller networks and singular nodes. Some of my highest BC values are in the small networks (that are around 5/6 proteins big). Can I discount the smaller networks that are not connected to the main network or is that not scientific?




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