depmap

Query DepMap for gene dependency scores and drug sensitivity across cancer cell lines.

1|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/yf8578/clawomics --skill depmap-yf8578
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: depmap
Source: https://github.com/yf8578/clawomics/tree/main/skills/depmap
Command: npx skills add https://github.com/yf8578/clawomics --skill depmap-yf8578

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps researchers identify critical genes and vulnerabilities in cancer cell lines by querying the Cancer Dependency Map (DepMap) database.

Core Features & Use Cases

  • Gene Dependency Scores: Retrieve CRISPR knockout scores for genes across hundreds of cancer cell lines.
  • Biomarker Discovery: Identify genomic features (mutations, expression) that predict sensitivity to gene knockouts.
  • Synthetic Lethality: Find gene pairs where the loss of one is tolerated, but the loss of both is lethal, suggesting novel therapeutic strategies.
  • Use Case: Investigate if a specific gene is essential in KRAS-mutant lung cancer cell lines to identify potential therapeutic targets.

Quick Start

Use the depmap skill to find cell lines selectively dependent on the gene 'KRAS' in lung cancer.

Frequently Asked Questions about depmap

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

FAQPage Schema
How do I find cancer cell lines selectively dependent on a specific gene using CRISPR screens?

To find cancer cell lines dependent on a specific gene, you can query CRISPR knockout scores from the DepMap database to retrieve gene effect profiles and identify cancer-specific vulnerabilities across hundreds of cell lines.

How does synthetic lethality analysis identify novel oncology drug targets?

Synthetic lethality analysis identifies drug targets by finding gene pairs where the loss of one is tolerated, but the loss of both is lethal, suggesting novel therapeutic strategies for cancer vulnerabilities.

Can I discover biomarkers that predict drug sensitivity from gene knockout data?

You can discover biomarkers predicting drug sensitivity by querying DepMap to identify genomic features like mutations or expression levels that correlate with sensitivity to specific gene knockouts in cancer cell lines.

What's the best way to validate oncology drug targets using RNAi screening data?

The best way to validate oncology drug targets is to retrieve drug sensitivity data and gene dependency scores from DepMap's RNAi screening data to confirm cancer-specific vulnerabilities across cell lines.

Does querying DepMap support identifying KRAS-mutant lung cancer vulnerabilities?

Querying DepMap supports identifying KRAS-mutant lung cancer vulnerabilities by retrieving gene dependency scores for specific cell lines to investigate if a gene is essential in that cancer context.

When should I not use DepMap gene effect profiles for target identification?

You should not use DepMap gene effect profiles when your research requires primary tumor data instead of cell line models, as the database relies on CRISPR and RNAi screening data from cultured cancer cell lines.