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string-protein-interaction-analysis-with-omicverse

Analyze protein-protein interaction networks from gene lists via STRING queries and pyPPI.

32|5|Updated Mar 12, 2026
Search Tags:#bioinformatics#omicverse#network-analysis#ppi#protein-interaction#string-db
One-click install
npx skills add https://github.com/omicverse/omicclaw --skill string-protein-interaction-analysis-with-omicverse-omicverse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: string-protein-interaction-analysis-with-omicverse
Source: https://github.com/omicverse/omicclaw/tree/main/src/omicverse_skills/skills/bulk-stringdb-ppi
Command: npx skills add https://github.com/omicverse/omicclaw --skill string-protein-interaction-analysis-with-omicverse-omicverse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rapidly turning a bulk gene list into an interpretable protein–protein interaction network is time consuming and error-prone due to species mapping, symbol mismatches, sparse connectivity, and styling requirements for publication-ready figures. This Skill centralizes STRING queries, network construction, optional expansion with predicted partners, and styled visualization so users can move from gene list to network figure with validation and troubleshooting guidance.

Core Features & Use Cases

  • STRING API integration and validation: query STRING for interactions while enforcing species NCBI taxonomy IDs and symbol formats to avoid empty results.
  • Network construction and expansion: build PPI graphs with pyPPI and optionally expand sparse networks using STRING's top predicted partners via add_nodes.
  • Styled visualization and export: apply group metadata (gene_type_dict and gene_color_dict) for publication-ready network plots and export edge tables for downstream analysis.
  • Use Cases: yeast fatty-acid gene interaction mapping, human DEG PPI network construction with predicted partner expansion, and exporting mouse edge tables colored by modules.

Quick Start

Run a STRING interaction query for my gene list with the correct species taxonomy ID and plot the styled PPI network using provided gene_type_dict and gene_color_dict.

Frequently Asked Questions about string-protein-interaction-analysis-with-omicverse

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a protein-protein interaction network from a gene list using STRING?▼

To build a protein-protein interaction network from a gene list, this Skill queries STRING using pyPPI while enforcing species NCBI taxonomy IDs and matching symbol formats. It constructs the PPI graph and applies provided metadata for styled visualization.

Why does my STRING protein interaction query return empty results?▼

STRING protein interaction queries return empty results when gene symbols do not match the target species NCBI taxonomy ID. This Skill validates symbol formats and species mapping to avoid mismatches, ensuring successful network construction from your bulk gene list.

Can I expand a sparse PPI network with predicted partners from STRING?▼

Yes, you can expand a sparse PPI network with predicted partners from STRING. By configuring the add_nodes parameter, this Skill retrieves STRING's top predicted interaction partners to enrich sparse connectivity and generate a more comprehensive network.

How do I export a STRING edge table for downstream analysis?▼

You can export a STRING edge table for downstream analysis directly from the constructed PPI graph. This Skill generates and exports interaction edge tables alongside publication-ready network plots styled with gene_type_dict and gene_color_dict.

What is needed to plot a publication-ready PPI network with gene metadata?▼

To plot a publication-ready PPI network, you need to provide gene_type_dict and gene_color_dict metadata for styling. This Skill uses these dictionaries during visualization to map gene groups and apply distinct colors to the STRING interaction network.

Does this PPI network analysis tool work for non-human species like yeast?▼

Yes, this PPI network analysis tool works for non-human species like yeast by applying species-specific gene panels. It requires the correct NCBI taxonomy ID to ensure accurate STRING interaction mapping for model organisms and human studies.

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