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Co-expression Network

The Co-expression tab visualizes gene correlation networks computed from your normalised count data. Unlike the PPI tab (which requires an external API), this report works for any organism — no internet or STRING database needed.

How It Works

Pairwise Pearson correlations are computed between significant DEGs using log2-transformed normalised counts. Gene pairs above the correlation threshold are displayed as a network.

Controls

Control Range Default Description
Max DEGs 10–200 50 Number of top DEGs (by adjusted p-value) to include
Min |correlation| 0.0–1.0 0.70 Minimum absolute Pearson r to draw an edge
Max edges 10–500 100 Maximum number of edges to display

Network Graph

  • Nodes = genes, colored by regulation direction (red = Up, blue = Down, grey = Other; uses sidebar Up/Down/Others colors)
  • Node size = scales from the sidebar Dot Size setting, growing with the number of connections (degree)
  • Node labels = preferred gene name when available, otherwise gene ID; use the sidebar Font color setting
  • Red edges = positive correlation (co-expressed; uses sidebar Up color)
  • Blue edges = negative correlation (inversely expressed; uses sidebar Down color)
  • Color legend = displayed on the right side of the graph, showing node direction categories (Up-regulated, Down-regulated, Other) and edge correlation types (Positive, Negative). Click a legend entry to toggle visibility.

Data Tables

  • Hub Genes — Top connected genes ranked by number of connections, with direction, log2FC, and adjusted p-value
  • Co-expression Edges — All gene pairs with their Pearson correlation values
  • Correlation Matrix — Heatmap of pairwise correlations among connected genes

Tip

Lower the "Min |correlation|" slider to discover weaker but potentially meaningful co-expression patterns. Raise it to focus on the strongest relationships.