Table 3 Methods used to assess co-expression networks
From: Exploiting single-cell expression to characterize co-expression replicability
Assessment | Property tested | Method and interpretation |
|---|---|---|
Co-expression performance | Functional connectivity of each GO group | • Neighbor voting for GO functions, threefold cross-validation |
• AUROC >0.5 means the genes within the GO group have greater connectivity than may be expected by chance | ||
Within-network semantic similarity (thresholded) | Functional connectivity of the network | • Number of GO functions in common among top 1 % of network connections |
• A higher value indicates greater functional similarity among top connections | ||
Between-network similarity (thresholded) | Topology | • Jaccard index (intersect/union) over top 1 % connections |
• Values closer to 1 imply greater similarity between networks | ||
Co-expression performance after aggregation | Replicability of functional connectivity | • Neighbor voting for GO functions as datasets are added together to form aggregate networks |
• Improvement with aggregation suggests specific replicability of functional connections | ||
Aggregate connectivity distributions | Replicability of topology | • Rank standardized networks (with uniform distributions) are added together to form an aggregate network, then the standard deviation across all co-expression values is measured |
• Higher variance indicates greater replicability of topology among networks |