depmap

Identify cancer-specific gene dependencies and synthetic lethal partners from DepMap datasets.

74|5|Updated Dec 10, 2025
One-click install
npx skills add https://github.com/dralkh/seerai --skill depmap-dralkh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: depmap
Source: https://github.com/dralkh/seerai/tree/main/skills/depmap
Command: npx skills add https://github.com/dralkh/seerai --skill depmap-dralkh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps researchers identify cancer-specific gene dependencies, synthetic lethal partners, and drug response signals from DepMap data without manually piecing together multiple datasets.

Core Features & Use Cases

  • Gene dependency analysis: Compare Chronos or RNAi scores across cell lines to find essential genes and selective vulnerabilities.
  • Biomarker discovery: Test whether mutations, expression, or copy number changes predict dependency on a target gene.
  • Systematic review support: Use DepMap annotations and analysis workflows to prioritize targets for oncology research and validate hypotheses across cancer lineages.
  • Use case: A researcher studying KRAS-mutant lung cancer can quickly find which genes are most selectively essential in that lineage and cross-check them against mutation and expression patterns.

Quick Start

Use the depmap skill to identify the most selective gene dependencies for a chosen cancer lineage and summarize the top candidate vulnerabilities.

Frequently Asked Questions about depmap

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

FAQPage Schema
How do I identify synthetic lethal partners using DepMap CRISPR and RNAi data?▼

To identify synthetic lethal partners using DepMap CRISPR and RNAi data, compare Chronos dependency scores across cell lines to find selectively essential genes. This pinpoints cancer-specific vulnerabilities by statistically contrasting mutant and wild-type groups.

What is gene dependency analysis for cancer target validation?▼

Gene dependency analysis for cancer target validation is the process of evaluating Chronos scores to determine if a gene is selectively essential in specific cancer lineages. It validates oncology research hypotheses by aligning cell line metadata with dependency patterns.

Can I discover biomarkers for drug sensitivity from gene expression and copy number data?▼

Yes, you can discover biomarkers for drug sensitivity from gene expression and copy number data. The workflow involves testing whether mutations, expression changes, or copy number alterations predict dependency on a specific target gene across cancer lineages.

Does pan-cancer essentiality analysis require statistical comparison of mutant versus wild-type groups?▼

Yes, pan-cancer essentiality analysis requires statistical comparison of mutant versus wild-type groups. It relies on Chronos-based dependency interpretation and cell line metadata alignment to systematically prioritize targets and validate hypotheses across cancer lineages.

What is the best way to find cancer-specific gene dependencies without manually piecing together datasets?▼

The best way to find cancer-specific gene dependencies without manually piecing together datasets is to apply integrated analysis workflows across CRISPR, RNAi, mutation, and expression data. This systematically identifies selective vulnerabilities and drug response signals.