normal-tissue-expression-for-gene

Resolve normal tissue expression for a single gene using GTEx data.

64|12|Updated Apr 7, 2026

Search Tags:#visualization #data-analysis #gene-expression #barplot #gtex #tissue-expression

Ready to run

npx skills add https://github.com/MDhewei/bioinfor-claw --skill normal-tissue-expression-for-gene

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: normal-tissue-expression-for-gene
Source: https://github.com/MDhewei/bioinfor-claw/tree/main/gene-centered-analysis/normal-tissue-expression-by-gene
Command: npx skills add https://github.com/MDhewei/bioinfor-claw --skill normal-tissue-expression-for-gene

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Retrieve and summarize normal tissue expression for a single human gene using GTEx, including full tissue-level expression, publication-quality barplot output, and a simple expression-pattern classification such as universally expressed, tissue-specific, mixed, or non-expressed.

Core Features & Use Cases

Retrieve GTEx median tissue expression for a single gene and present tissue-level data in a sortable table.
Classify expression pattern into universally-expressed, tissue-specific, mixed, non-expressed, or no-data, with a simple interpretation.
Generate publication-quality visualizations (barplots) and produce publication-ready outputs (PNG/PDF, TSV, summary text).
Output deterministic artifacts including: tissue expression table, summary text, summary TSV, and plots for easy downstream reporting.

Quick Start

Run the GTEx single-gene expression workflow by executing python scripts/normal_tissue_expression_for_gene.py --gene "<GENE>" --outdir <OUTPUT_DIR>.

Frequently Asked Questions about normal-tissue-expression-for-gene

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

FAQPage Schema

How do I get normal tissue gene expression data from GTEx for a single gene?▼

To retrieve normal tissue gene expression from GTEx, run the script with a valid gene symbol and output directory. The workflow resolves the gene to a canonical GENCODE ID, fetches median tissue expression, computes log2(TPM+1), and outputs a tissue-level table, summary text, TSV, and barplots.

What does GTEx tissue-specific gene expression classification mean?▼

GTEx tissue expression classification categorizes a gene's cross-tissue distribution into universally-expressed, tissue-specific, mixed, non-expressed, or no-data based on normalized log2(TPM+1) values. This helps determine whether a gene's expression pattern is broad or restricted to specific tissues.

Can I generate publication-ready barplots for gene expression analysis using Python?▼

Yes, this workflow generates publication-quality barplots in both PNG and PDF formats for gene expression analysis. It uses matplotlib and pandas to visualize cross-tissue distribution and outputs deterministic artifacts suitable for downstream reporting.

Do I need GTEx API access to retrieve tissue-level expression data?▼

Yes, GTEx API access is required to retrieve tissue-level expression data. The workflow depends on the requests library to query the API for median tissue expression values, which are then normalized and classified into expression pattern categories.

What is the best way to analyze cross-tissue expression distribution for a single gene?▼

The best way to analyze cross-tissue expression distribution is using a workflow that resolves the gene to a canonical GENCODE ID, normalizes GTEx median expression data to log2(TPM+1), classifies the expression pattern, and produces a comprehensive report with tables and barplots.

Why does my GTEx gene expression query return no data for some genes?▼

GTEx gene expression queries return no data when the input gene symbol cannot be resolved to a canonical GENCODE ID or lacks tissue-level expression records. The workflow classifies such cases as no-data or non-expressed in the summary output.