google-deepmind/science-skills

gtex-database

Use when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/google-deepmind/science-skills --skill gtex-database

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

GTEx Database Integration

This skill retrieves transcriptomics data (RNA expression baselines) and expression Quantitative Trait Loci (eQTLs) from the GTEx Portal API V2. It provides access to median TPM (Transcripts Per Million) values for genes and significant eQTLs for variants across 54 human tissue sites.

Prerequisites

  1. `uv`: Read the uv skill and follow its Setup instructions to ensure

uv is installed and on PATH.

  1. User Notification: If .licenses/gtexdatabaseLICENSE.txt does not

already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://gtexportal.org/home/license and https://gtexportal.org/home/documentationPage#gtexApi, then (2) create the file recording the notification text and timestamp.

When to Use

Use this skill when you need to:

  • Map a gene symbol to its Versioned GENCODE ID.
  • Retrieve the baseline median expression level (in TPM) of a gene across

various tissues.

  • Find the top tissues where a particular gene is most highly expressed.
  • Fetch significant single-tissue eQTLs for a variant or within a chromosomal

window.

  • Get all significant eQTLs associated with a specific gene.
  • Contextualise a variant within GWAS loci using eQTL data.

Do NOT use when you need to:

  • Query for protein-level expression or post-translational modifications

(PTMs). GTEx only measures mRNA abundance.

  • Query gene expression in diseased tissues (e.g., tumor samples, cirrhosis).

GTEx is a baseline atlas of normal, non-diseased tissues.

  • Query embryonic or fetal gene expression. GTEx donors are adults only.

Core Rules

CRITICAL: You MUST respect GTEx Portal API Terms of Use.

  • Use the Wrapper: ALWAYS execute the provided helper scripts to query the

database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.

  • Limit requests to maximum 250 items per page where applicable.
  • Notification: If this skill is used, ensure this is mentioned in the

output.

Command Selection Guide

Pick the right command on the first try. Match the user's input to the correct subcommand below.

  • Map a gene symbol to GENCODE ID: resolve-gencode-id
  • Get median expression (TPM) for a gene: get-median-expression
  • Find tissues with highest expression for a gene: get-top-expressed-tissues
  • Get all eQTLs for a specific gene: get-gene-eqtls
  • Find eQTLs within a chromosomal region: get-eqtls-in-region

Quick Start

bash
# Map the TNF gene symbol to its GENCODE ID
uv run scripts/gtex_cli.py resolve-gencode-id TNF --output /tmp/tnf_id.json

# Get median expression of a gene by GENCODE ID
uv run scripts/gtex_cli.py get-median-expression ENSG00000232810.2 --output /tmp/tnf_expr.json

All subcommands write JSON to disk. Always save output in the /tmp/ directory. The default output file is /tmp/gtex_output.json if --output is not specified.

Commands

1. resolve-gencode-id — Gene Symbol → GENCODE ID

Maps a standard gene symbol (e.g., "JUN", "TNF") to its Versioned GENCODE ID. This ID is required for all other expression and eQTL calls.

bash
uv run scripts/gtex_cli.py resolve-gencode-id TNF --output /tmp/tnf_id.json

Arguments:

  • gene_symbol (positional): The standard gene symbol (e.g., "TNF").
  • --output: Output file path (default: /tmp/gtex_output.json).

2. get-median-expression — Get Median Expression (TPM)

Retrieves the median TPM for a gene across all 54 GTEx tissue sites or specified tissues.

bash
uv run scripts/gtex_cli.py get-median-expression ENSG00000232810.2 \
  --tissues "Whole Blood,Spleen" --output /tmp/expr.json

Arguments:

  • gencode_id (positional): The Versioned GENCODE ID.
  • --tissues: Comma-separated list of tissue IDs (optional, defaults to all

54 tissues).

  • --output: Output file path (default: /tmp/gtex_output.json).

3. get-top-expressed-tissues — Get Top Expressed Tissues

Returns the n tissues with the highest median expression for the target gene.

bash
uv run scripts/gtex_cli.py get-top-expressed-tissues ENSG00000232810.2 \
  --n 5 --output /tmp/top_tissues.json

Arguments:

  • gencode_id (positional): The Versioned GENCODE ID.
  • --n: Number of top tissues to return (default: 5).
  • --output: Output file path.

4. get-gene-eqtls — Get All eQTLs for a Gene

Returns every significant eQTL associated with the gene across specified tissues.

bash
uv run scripts/gtex_cli.py get-gene-eqtls ENSG00000232810.2 \
  --tissues "Whole Blood" --output /tmp/eqtls.json

Arguments:

  • gencode_id (positional): The Versioned GENCODE ID.
  • --tissues: Comma-separated list of tissue IDs (optional, defaults to all).
  • --output: Output file path.

5. get-eqtls-in-region — Get eQTLs in Chromosomal Region

Returns all significant single-tissue eQTLs within a chromosomal window (up to 8Mb).

bash
uv run scripts/gtex_cli.py get-eqtls-in-region chr17 7000000 7100000 "Esophagus - Muscularis" \
  --output /tmp/region_eqtls.json

Arguments:

  • chromosome (positional): Chromosome name (e.g., chr17).
  • start (positional): Start position.
  • end (positional): End position (max 8Mb from start).
  • tissue_id (positional): The target tissue ID.
  • --output: Output file path.

Typical Workflows

Identify highest expressing tissues for a gene

bash
# Step 1: Map symbol to GENCODE ID
uv run scripts/gtex_cli.py resolve-gencode-id GATA4 --output /tmp/gata4_id.json

# Step 2: Query for top tissues using the resolved ID
uv run scripts/gtex_cli.py get-top-expressed-tissues <gencode_id> --n 5 \
  --output /tmp/gata4_top.json

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