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tooluniverse-cell-line-profiling

Profiles and ranks cancer cell lines using DepMap, Cellosaurus, COSMIC, and PharmacoDB data.

1.7k|254|Updated Mar 3, 2025
Search Tags:#model selection#cancer#drug sensitivity#DepMap#cell line#crispr dependency#mutation profiling
One-click install
npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-cell-line-profiling
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tooluniverse-cell-line-profiling
Source: https://github.com/mims-harvard/ToolUniverse/tree/main/plugins/tooluniverse/skills/tooluniverse-cell-line-profiling
Command: npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-cell-line-profiling

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Choosing the right cancer cell line for an experiment requires cross-referencing mutations, gene dependencies, drug sensitivities, and identity records scattered across multiple databases, which is slow and error-prone when done manually.

Core Features & Use Cases

  • Identity Verification: Confirms cell line identity, species, STR profile, and contamination flags via Cellosaurus and DepMap.
  • Molecular & Dependency Profiling: Retrieves mutations from COSMIC and cBioPortal CCLE, plus per-cell-line CRISPR Chronos dependency scores through a bundled DepMap download script.
  • Drug Sensitivity & Druggability: Pulls IC50/AAC data from PharmacoDB, synergy scores from SYNERGxDB, and druggable targets from DGIdb and OpenTargets.
  • Use Case: Ask which cell line best models KRAS-mutant pancreatic cancer and receive a ranked recommendation with weighted scoring across mutation match, dependency, drug data, and practical culture factors.

Quick Start

Ask the agent which cancer cell line you should use to study a specific gene or cancer type and request a ranked recommendation with rationale.

Frequently Asked Questions about tooluniverse-cell-line-profiling

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

FAQPage Schema
How do I choose a cancer cell line for studying a specific gene?▼

Provide the cancer type and gene of interest, and the workflow searches DepMap for candidate lines, checks mutations via COSMIC and cBioPortal CCLE, and ranks lines by mutation match, gene dependency, and drug sensitivity data. The output is a scored recommendation table with rationale.

How do I get DepMap CRISPR dependency scores per cell line?▼

Run the bundled script scripts/depmap_gene_dependency.py with a gene symbol or cell line name. It downloads the DepMap Public CRISPRGeneEffect.csv and Model.csv once, caches them, and reports Chronos scores where values below -0.5 indicate dependency.

Which databases does this cell line profiling workflow use?▼

It cross-references DepMap, Cellosaurus, COSMIC, PharmacoDB, cBioPortal CCLE, CellMarker, HPA, SYNERGxDB, DGIdb, OpenTargets, and STRING. Cell line name serves as the common key, with Cellosaurus synonyms resolving naming differences.

Why does DepMap_get_gene_dependencies not return per-cell-line scores?▼

The ToolUniverse DepMap tool returns only gene metadata such as HGNC and Ensembl IDs, not Chronos scores. Use the bundled depmap_gene_dependency.py script, which pulls the bulk CRISPRGeneEffect.csv release directly from depmap.org.

What are the limitations of the HPA expression lookup for cell lines?▼

HPA comparative expression supports only ten cell lines: hela, mcf7, a549, hepg2, jurkat, pc3, rh30, siha, u251, and ishikawa. For any other line, the HPA step is skipped and noted as a limitation in the report.

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