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Network layout algorithm selection

Skill HolobiomicsLab/asb-skill-collections/collections/metabolomics/v2/skills/network-layout-algorithm-selection

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Install
npx -y skills add HolobiomicsLab/asb-skill-collections --skill network-layout-algorithm-selection

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Use when you have a network object (nodes and edges) loaded in MetaNet and need to compute 2D or 3D spatial coordinates for visualization. This skill is necessary before any network plotting step. Choose this when your network structure (e.

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SKILL.md

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network-layout-algorithm-selection

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

Summary

Select and apply an appropriate layout algorithm from MetaNet's 40+ options to assign spatial coordinates to network nodes for static or interactive visualization. The choice of algorithm affects how node relationships are spatially represented and the interpretability of the resulting visualization.

When to use

You have a network object (nodes and edges) loaded in MetaNet and need to compute 2D or 3D spatial coordinates for visualization. This skill is necessary before any network plotting step. Choose this when your network structure (e.g., hierarchical, modular, scale-free, or random) and visualization context (static plot vs. interactive dashboard) are known or need to be explored.

When NOT to use

  • Network object is already pre-laid out and coordinates are fixed for reproducibility.
  • Visualization context requires 3D or time-varying coordinates not natively supported by the chosen layout.

Inputs

  • metanet network object (nodes and edges)
  • node identifiers (character vector)
  • edge list or adjacency structure

Outputs

  • coordinate table (x, y positions per node)
  • exported coordinates file (CSV or TSV format)

How to apply

Load your network object into MetaNet as a metanet class object. Evaluate your network's structural properties (hierarchy, modularity, density) and your visualization goal (exploratory vs. publication-ready, static vs. interactive). Select an appropriate layout algorithm from MetaNet's 40+ options, which include force-directed layouts for organic exploration, hierarchical layouts for ranked data, circular layouts for symmetry, and spatstat layouts for spatial annotation. Apply the chosen layout via MetaNet's layout function (e.g., c_net_layout() or g_layout_*() functions). Extract the resulting coordinate matrix (x, y columns paired with node identifiers) and verify that all nodes have valid coordinates and no duplicates exist.

Related tools

  • MetaNet (Provides 40+ layout algorithms and the layout application function for coordinate computation) — https://github.com/Asa12138/MetaNet
  • igraph (Underlying graph representation and some layout algorithm implementations)
  • spatstat (Spatial layout algorithms available within MetaNet for spatially annotated networks)

Examples

g_layout_treemap(multi1_module) -> coors1; c_net_plot(multi1_module, coors1, legend = F, main = "", plot_module = T, mark_module = T)

Evaluation signals

  • All nodes in the network are assigned unique (x, y) coordinate pairs with no missing or infinite values.
  • Coordinates fall within a bounded range appropriate for the chosen algorithm (e.g., force-directed layouts converge; circular layouts cluster on a circle).
  • Node separation and edge crossing patterns match the expected visual structure for the chosen algorithm (e.g., hierarchical layouts show layering; force-directed layouts minimize edge crossings).
  • Exported coordinate file contains exactly one row per unique node with matching node identifiers between the network object and coordinate table.
  • Subsequent visualization using c_net_plot() with these coordinates produces a legible and interpretable layout without visual artifacts (overlapping labels, nodes outside canvas).

Limitations

  • Layout quality depends on network size, density, and structure; very large or densely connected networks may require parameter tuning or subgraph extraction.
  • Some layout algorithms (e.g., force-directed) are stochastic and may produce different coordinate assignments across runs; set a random seed for reproducibility.
  • Interactive platforms may apply additional coordinate transformations or zoom/pan that differ from static exports.
  • Layout algorithm performance varies: force-directed scales well to ~10,000 nodes but becomes slow beyond that; hierarchical layouts assume acyclic or weakly cyclic structure.

Evidence

  • [full_text] MetaNet provides over 40 layout algorithms that can be applied to position nodes in a network for visualization on both static and interactive platforms.: "MetaNet provides over 40 layout algorithms that can be applied to position nodes in a network for visualization on both static and interactive platforms."
  • [full_text] The workflow shows applying layout algorithms to compute node coordinates and exporting them as tabular files.: "Select and apply one of the 40+ available layout algorithms (e.g., force-directed, hierarchical, circular) via MetaNet's layout function. Extract computed node coordinates (x, y positions) from the"
  • [readme] MetaNet's architecture includes a dedicated Layout module as a core functional component.: "Its architecture comprises several core functional modules: Calculation, Manipulation, Layout, Visualization, Topology analysis, Module analysis, Stability analysis, and I/O (Figure 1A), supporting"
  • [readme] Documentation describes various layout function families including basic, spatstat, and multi-level variants.: "[Detailed usage includes sections for] Basic layouts, spatstat layouts, Group and multi-level layouts"
  • [readme] The README provides a concrete example using layout functions to compute and visualize coordinates.: "g_layout_treemap(multi1_module) -> coors1; c_net_plot(multi1_module, coors1, legend = F, main = "", plot_module = T, mark_module = T, vertex.color = get_cols())"

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