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bulkrna-ppi-network

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Load when querying STRING for the protein-protein interaction subgraph induced by a bulk RNA-seq DEG list and finding hub genes. Skip for pathway enrichment of the same list (use bulkrna-enrichment) or for de novo co-expression network discovery (use bulkrna-coexpression).

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bulkrna-ppi-network

When to use

Run after bulkrna-de to ask "what does the STRING PPI subgraph induced by my DEG list look like, and which proteins are central?". Queries the public STRING API (no installation needed), constructs the induced subgraph, and ranks hub proteins by degree centrality.

Inputs & Outputs

InputFormatRequired
Gene list / DE results.csv (gene names)yes (or --demo)
--species NCBI taxonintdefault 9606 (human); 10090 for mouse
--score-thresholdint 0–1000default 400 (STRING "medium" confidence)
--top-nintdefault 20 (top-degree hubs to report)
OutputPathNotes
Edge listtables/interaction_edges.csvsource / target / score
Node centralitytables/node_centrality.csvper-gene degree / betweenness / closeness / hub_score
Hub genestables/hub_genes.csvtop-N from node_centrality by hub_score
Network figurefigures/ppi_network.pngNetworkX layout
Hub-gene barplotfigures/hub_genes_barplot.pngtop-N by hub_score
Reportreport.md + result.jsonsummary keys: n_genes, n_edges, n_connected, n_isolated, mean_degree

Flow

  1. Parse gene list from --input (treats first column as gene names).
  2. Query STRING API with species + score_threshold.
  3. On API failure, fall back silently to built-in demo edges (bulkrna_ppi_network.py:118 warns "STRING API failed (...) — using built-in demo edges").
  4. Build NetworkX graph; compute degree centrality.
  5. Report top-N hubs; render network + degree-distribution figures.

Gotchas

  • STRING-API-failure fallback is to DEMO edges, not a smaller real query. bulkrna_ppi_network.py:118 catches any API exception and substitutes the built-in toy network. This means a transient network outage produces output that looks normal but is unrelated to the user's gene list. The summary dict does not record which edge source ran — grep the run's stderr for "STRING API failed" to detect a silent fallback before reporting downstream conclusions.
  • --score-threshold is on STRING's 0–1000 scale, not 0–1. Default 400 is STRING's "medium" confidence band; 700 is "high"; 900 is "highest". Passing 0.4 (a float) is silently coerced to 0 and pulls every edge in the database.
  • --species is the NCBI taxon ID (default 9606 human, 10090 mouse). Passing the string "human" or "mouse" raises a type error from int(args.species). STRING also requires the species to be in its supported list — exotic taxa fail at the API layer.
  • Gene-name namespace must match STRING's expectations. STRING uses HGNC symbols for human, MGI symbols for mouse. Feeding Ensembl IDs gives ~zero hits and a near-empty network — pre-run bulkrna-geneid-mapping to convert.

Key CLI

python omicsclaw.py run bulkrna-ppi-network --demo
python omicsclaw.py run bulkrna-ppi-network \
  --input de_significant.csv --output results/
python omicsclaw.py run bulkrna-ppi-network \
  --input de_significant.csv --output results/ \
  --species 10090 --score-threshold 700 --top-n 30

See also

  • references/parameters.md — every CLI flag and tuning hint
  • references/methodology.md — STRING query format, hub-gene definition (degree centrality)
  • references/output_contract.md — exact output directory layout
  • Adjacent skills: bulkrna-de (upstream — DEG source), bulkrna-enrichment (parallel: pathway view of the same list), bulkrna-coexpression (parallel: de novo co-expression network from the count matrix), bulkrna-geneid-mapping (run upstream to convert IDs to HGNC/MGI)