coexpression-for-gene

Identify genes co-expressed with a query gene across TCGA and GTEx datasets.

64|12|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/MDhewei/bioinfor-claw --skill coexpression-for-gene
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: coexpression-for-gene
Source: https://github.com/MDhewei/bioinfor-claw/tree/main/gene-centered-analysis/coexpression-for-gene
Command: npx skills add https://github.com/MDhewei/bioinfor-claw --skill coexpression-for-gene

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, matplotlib, scipy, requests, and includes scripts (resource) components.

What problem does it solve?

Co-expression for Gene identifies genes whose expression patterns correlate with a query gene across TCGA PanCancer Atlas patient samples and GTEx normal tissues, enabling discovery of functionally related genes and co-expression networks.

Core Features & Use Cases

  • Data-driven discovery of gene modules by correlating a query gene with all other genes across selected datasets.
  • Supports TCGA pan-cancer analysis via cBioPortal REST API and GTEx with a user-provided expression matrix.
  • Outputs include coexpression_results.tsv, top_coexpressed.png, coexpression_network.png, and an optional GO enrichment/summary report.

Quick Start

Provide a gene symbol and dataset options to compute its co-expression across TCGA and GTEx data.

Frequently Asked Questions about coexpression-for-gene

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

FAQPage Schema
How do I find genes co-expressed with a specific gene across TCGA samples?

To find co-expressed genes across TCGA samples, provide a gene symbol to compute Pearson or Spearman correlations against the TCGA PanCancer Atlas dataset, requiring internet access to query the cBioPortal REST API for expression data.

Can I use my own GTEx expression matrix to identify tissue-specific co-expression?

Yes, you can perform tissue-specific co-expression analysis by providing a custom GTEx expression matrix, computing correlations for your query gene without needing external API access, yielding results and visualizations.

What is the difference between Pearson and Spearman correlation for gene co-expression analysis?

Pearson correlation measures linear relationships between gene expression profiles, while Spearman evaluates monotonic rank-based associations; both methods are supported and apply FDR correction to output statistically significant co-expressed genes.

What outputs and visualizations are generated from a gene co-expression query?

A gene co-expression query generates a results TSV file, a top coexpressed genes plot, a co-expression network visualization, and an optional GO enrichment summary report detailing functional relationships.

Do I need internet access to run TCGA pan-cancer co-expression analysis?

Yes, running TCGA pan-cancer co-expression analysis requires internet access to fetch expression data from the cBioPortal REST API, whereas analyzing a user-provided GTEx expression matrix operates entirely locally.