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Omics network visualization preparation

Skill HolobiomicsLab/asb-skill-collections/collections/metabolomics/v2/skills/omics-network-visualization-preparation

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Install
npx -y skills add HolobiomicsLab/asb-skill-collections --skill omics-network-visualization-preparation

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Use when after constructing a correlation-based network from omics data (nodes and edges defined), when you need to assign visual positions to nodes for rendering.

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SKILL.md

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Apply layout algorithms to assign spatial coordinates to network nodes for visualization

License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution. <!-- asb-license-banner -->

Summary

This skill involves selecting and applying one of MetaNet's 40+ layout algorithms (force-directed, hierarchical, circular, or others) to compute two-dimensional spatial coordinates (x, y positions) for network nodes, enabling subsequent visualization on static or interactive platforms.

When to use

After constructing a correlation-based network from omics data (nodes and edges defined), when you need to assign visual positions to nodes for rendering. Use this skill when the network object exists but lacks computed spatial coordinates, or when you want to try alternative layout algorithms to improve interpretability of multi-omics network structure.

When NOT to use

  • Network object has not yet been constructed—build the network first using c_net_build() or multi_net_build().
  • Nodes already have pre-assigned layout coordinates from external source—apply layout only when coordinates need computation or re-assignment.
  • Goal is topological analysis only (e.g., degree, centrality, modularity) and visualization is not required.

Inputs

  • Network object (igraph or metanet class) with defined nodes and edges
  • Correlation coefficients and network topology (already constructed)

Outputs

  • Coordinate table (data.frame or matrix) with node identifiers and x, y spatial positions
  • Exported coordinate file (CSV or TSV format, optional)

How to apply

Load a network object (containing edges and nodes) into MetaNet in R. Select an appropriate layout algorithm from MetaNet's 40+ options based on your network structure and interpretation goals—for example, use force-directed layouts for general correlation networks, hierarchical layouts for layered omics data, circular layouts for comparison, or spatstat and group-based layouts for multi-level omics networks. Call MetaNet's layout function with the network and algorithm choice to compute node coordinates. Extract the resulting x, y coordinate table from the layout output (typically as a data.frame or matrix with node identifiers and their assigned positions). Validate that coordinates are numeric, non-redundant, and span a reasonable 2D space before export.

Related tools

  • MetaNet (Primary tool providing 40+ layout algorithms and coordinate computation functions for network node positioning) — https://github.com/Asa12138/MetaNet
  • R (Execution environment for MetaNet and layout algorithm computation)
  • igraph (Underlying graph structure and layout infrastructure that MetaNet builds upon)
  • pcutils (Utility package supporting MetaNet data transformation and manipulation) — https://github.com/Asa12138/pcutils

Examples

library(MetaNet); net <- c_net_build(cor, r_threshold = 0.65); coors <- g_layout_treemap(net); c_net_plot(net, coors)

Evaluation signals

  • Coordinate table contains exactly one x and one y value per node, with no missing or infinite values.
  • Node identifiers in the coordinate table match those in the original network object (one-to-one correspondence).
  • Computed coordinates span a non-trivial 2D space (not collapsed to a line or single point) unless the network structure requires it.
  • When visualized with c_net_plot() using the computed coordinates, the resulting plot shows no node overlap artifacts and reflects the network topology logically (e.g., highly connected nodes are not isolated, module structure is apparent).
  • Layout computation completes without errors and produces consistent coordinates across re-runs with the same algorithm and parameters.

Limitations

  • Layout algorithms are deterministic or use random seeds; results may vary slightly across runs unless a seed is fixed, particularly for force-directed layouts.
  • Some layouts (e.g., force-directed) may perform poorly on very large networks (>5,000 nodes) or highly disconnected graphs, as noted in benchmarking literature on network visualization.
  • Multi-omics networks with distinct layer structures may require specialized group or multi-level layouts (e.g., g_layout_treemap) rather than standard algorithms to prevent layer overlap.
  • Coordinate computation does not validate network quality or correctness—garbage network input will produce geometrically valid but meaningless coordinates.

Evidence

  • [intro] providing over 40 layout algorithms, rich annotation utilities, and visualization options compatible with both static and interactive platforms: "providing over 40 layout algorithms, rich annotation utilities, and visualization options compatible with both static and interactive platforms"
  • [other] Select and apply one of the 40+ available layout algorithms (e.g., force-directed, hierarchical, circular) via MetaNet's layout function.: "Select and apply one of the 40+ available layout algorithms (e.g., force-directed, hierarchical, circular) via MetaNet's layout function"
  • [other] Extract computed node coordinates (x, y positions) from the layout output.: "Extract computed node coordinates (x, y positions) from the layout output"
  • [readme] Layout and Visualization — Basic layouts, spatstat layouts, Group and multi-level layouts: "Layout and Visualization — Basic layouts, spatstat layouts, Group and multi-level layouts"
  • [readme] Its architecture comprises several core functional modules: Calculation, Manipulation, Layout, Visualization, Topology analysis, Module analysis, Stability analysis, and I/O: "Its architecture comprises several core functional modules: Calculation, Manipulation, Layout, Visualization, Topology analysis, Module analysis, Stability analysis, and I/O"

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