depmap

Analyze DepMap Chronos scores to identify cancer cell line dependencies and drug targets.

22|4|Updated May 25, 2026
One-click install
npx skills add https://github.com/crazymsn/academic-skills --skill depmap-crazymsn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: depmap
Source: https://github.com/crazymsn/academic-skills/tree/main/academic-skills/depmap
Command: npx skills add https://github.com/crazymsn/academic-skills --skill depmap-crazymsn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

DepMap provides comprehensive gene dependency scores and cell line annotations to identify cancer-specific vulnerabilities and validate targets, enabling researchers to map essential genes and potential synthetic lethal interactions.

Core Features & Use Cases

  • Retrieve Chronos gene effect scores across hundreds of cancer cell lines to identify selective dependencies.
  • Analyze cell line metadata (DepMap_ID, lineage, primary_disease) to correlate dependencies with tissue types and mutations.
  • Perform biomarker-assisted analyses and co-essentiality screening to prioritize drug targets and synthetic lethality partners.

Quick Start

Query Chronos scores for a target gene across the DepMap panel and examine which cell lines show strong dependency, then assess selectivity by cancer type.

Frequently Asked Questions about depmap

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

FAQPage Schema
How do I identify synthetic lethality partners using cancer cell line gene dependency scores?

To identify synthetic lethality partners, you analyze Chronos gene effect scores across DepMap cell lines and correlate gene dependencies with specific biomarkers. This process filters and merges dependency data to reveal selective vulnerabilities and potential drug targets.

What is the best way to find selective gene dependencies across different cancer lineages?

Finding selective gene dependencies involves querying Chronos gene effect scores across the DepMap panel and merging them with sample metadata. By grouping cell lines by lineage or primary disease, you can summarize and assess which tissue types show strong target vulnerability.

Can I use biomarker-assisted analysis to prioritize drug targets from DepMap data?

Yes, you can perform biomarker-assisted analysis by merging Chronos gene effect data with cell line mutation and sample info. This approach reveals biomarker-driven targets and co-essentiality patterns to prioritize potential therapeutic vulnerabilities.

Do I need Python to process DepMap Chronos scores and sample info?

Yes, you need basic Python data processing to filter, merge, and summarize DepMap data. Access to Chronos scores and sample info files is required to manipulate the datasets and extract cancer cell line dependencies effectively.

How does co-essentiality screening work when mapping cancer-specific vulnerabilities?

Co-essentiality screening works by comparing gene dependency correlations across hundreds of cancer cell lines using Chronos scores. This analysis identifies genes with similar dependency patterns, validating targets and revealing potential synthetic lethal interactions.