String Ext Tools#

Configuration File: string_ext_tools.json Tool Type: Local Tools Count: 2

This page contains all tools defined in the string_ext_tools.json configuration file.

Available Tools#

STRING_get_enrichment (Type: STRINGExtTool)#

Perform functional enrichment analysis on a set of proteins using the STRING database. Tests whet…

STRING_get_enrichment tool specification

Tool Information:

  • Name: STRING_get_enrichment

  • Type: STRINGExtTool

  • Description: Perform functional enrichment analysis on a set of proteins using the STRING database. Tests whether the input protein list is statistically enriched for Gene Ontology terms, KEGG pathways, Reactome pathways, WikiPathways, InterPro domains, TISSUES, DISEASES, COMPARTMENTS, and other functional categories. Returns enriched terms with p-values, FDR-corrected q-values, and the matching proteins. Useful for interpreting gene lists from RNA-seq, GWAS, proteomics experiments.

Parameters:

  • identifiers (string) (required) Newline-separated list of protein identifiers (gene names or STRING IDs). Example: ‘BRCA1nBRCA2nTP53nATM’. Minimum 2 proteins, recommended 5-100 for meaningful enrichment.

  • species (integer) (optional) NCBI taxonomy ID (default 9606 for human). Examples: 9606 (human), 10090 (mouse), 7227 (fly), 6239 (worm).

  • background_string_identifiers ([‘string’, ‘null’]) (optional) Optional newline-separated background gene set. If not provided, the entire genome proteome is used as background.

Example Usage:

query = {
    "name": "STRING_get_enrichment",
    "arguments": {
        "identifiers": "example_value"
    }
}
result = tu.run(query)

STRING_get_functional_annotations (Type: STRINGExtTool)#

Get comprehensive functional annotations for a protein from STRING, grouped by category. limit an…

STRING_get_functional_annotations tool specification

Tool Information:

  • Name: STRING_get_functional_annotations

  • Type: STRINGExtTool

  • Description: Get comprehensive functional annotations for a protein from STRING, grouped by category. limit and offset are applied independently within every returned category; metadata.category_pagination reports each category’s total, returned count, has_more, and next_offset. Use category to page one high-cardinality source efficiently. Different from STRING functional enrichment, which tests a protein set statistically.

Parameters:

  • identifiers (string) (required) Protein identifier (gene name or STRING ID). Examples: ‘TP53’, ‘BRCA1’, ‘EGFR’, ‘9606.ENSP00000269305’.

  • species (integer) (optional) NCBI taxonomy ID (default 9606 for human). Examples: 9606 (human), 10090 (mouse), 7227 (fly), 6239 (worm).

  • category (string) (optional) Filter by annotation category. Options: ‘Process’ (GO BP), ‘Function’ (GO MF), ‘Component’ (GO CC), ‘KEGG’, ‘RCTM’ (Reactome), ‘WikiPathways’, ‘InterPro’, ‘Pfam’, ‘HPO’, ‘DISEASES’, ‘TISSUES’, ‘COMPARTMENTS’, ‘Keyword’. Leave null for all categories.

  • limit (integer) (optional) Page size within each annotation category (default 15).

  • offset (integer) (optional) Zero-based offset within each annotation category. Continue with category_pagination[category].next_offset.

Example Usage:

query = {
    "name": "STRING_get_functional_annotations",
    "arguments": {
        "identifiers": "example_value"
    }
}
result = tu.run(query)