Coexpression Module Tools

Configuration File: coexpression_module_tools.json Tool Type: Local Tools Count: 1

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

Available Tools

Coexpression_modules (Type: CoexpressionModuleTool)

Detect co-expression modules from a genes x samples expression matrix (WGCNA-style): builds a sof…

Coexpression_modules tool specification

Tool Information:

  • Name: Coexpression_modules

  • Type: CoexpressionModuleTool

  • Description: Detect co-expression modules from a genes x samples expression matrix (WGCNA-style): builds a soft-thresholded correlation network and partitions it into modules of co-regulated genes by modularity, returning each module’s genes and its module eigengene (first PC = per-sample summary profile). Pure-compute (NumPy + NetworkX). Simplified WGCNA (no TOM / dynamic tree cut).

Parameters:

  • expression (object) (required) {gene: [value_per_sample, …]} — a genes x samples expression matrix (log-normalized).

  • power ([‘integer’, ‘null’]) (optional) Soft-threshold exponent on |correlation| (default 6, the WGCNA scale-free default).

  • correlation_threshold ([‘number’, ‘null’]) (optional) Minimum |correlation| to connect two genes (default 0.5).

  • min_module_size ([‘integer’, ‘null’]) (optional) Minimum genes for a module to be reported (default 5).

Example Usage:

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