tooluniverse-cancer-genomics-tcga

Analyzes TCGA cancer cohorts for mutations, CNVs, survival, and variant clinical significance.

1.7k|254|Updated Mar 3, 2025
One-click install
npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-cancer-genomics-tcga
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tooluniverse-cancer-genomics-tcga
Source: https://github.com/mims-harvard/ToolUniverse/tree/main/plugins/tooluniverse/skills/tooluniverse-cancer-genomics-tcga
Command: npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-cancer-genomics-tcga

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cancer genomics research requires stitching together cohort construction, clinical metadata, somatic mutation profiling, copy number analysis, survival statistics, and variant annotation across multiple databases (GDC, Progenetix, OncoKB). This Skill provides a structured six-phase workflow that prevents common errors like interpreting pan-cancer mutation counts without cohort context.

Core Features & Use Cases

  • Cohort & Clinical Data: List GDC projects, search cases, and retrieve demographics, diagnoses, and treatments for any TCGA project (e.g., TCGA-BRCA).
  • Mutation & CNV Analysis: Query somatic mutations per gene and project, and search Progenetix for copy number amplifications or deletions by NCIt code and GRCh38 coordinates.
  • Survival & Variant Interpretation: Run Kaplan-Meier survival analysis split by mutation status with log-rank p-values, and annotate variants with OncoKB oncogenicity and FDA-level therapy evidence.
  • Use Case: Ask "What is the mutation frequency of TP53 in TCGA-LUAD and does it affect survival?" to get per-project mutation records, a survival comparison with p-value, and OncoKB clinical actionability in one workflow.

Quick Start

Ask the agent to analyze TP53 mutation frequency and survival impact in TCGA-BRCA using the cancer genomics workflow.

Frequently Asked Questions about tooluniverse-cancer-genomics-tcga

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

FAQPage Schema
How do I find mutation frequency of a gene in a specific TCGA cancer type?

Use GDC_get_ssm_by_gene with the gene_symbol and project_id (e.g., TCGA-LUAD) to get per-mutation records for that cancer type. GDC_get_mutation_frequency only returns pan-cancer totals, so always specify a project for cancer-specific frequencies.

How to run survival analysis by mutation status in TCGA?

Call GDC_get_survival with a project_id and gene_symbol to split the cohort into mutated versus wild-type groups. It returns donor-level Kaplan-Meier data with time, censoring status, and a log-rank p-value in overallStats.

What is the difference between GDC and Progenetix for cancer genomics?

GDC tools cover TCGA cohorts, clinical data, somatic mutations, and survival. Progenetix provides copy number variation data, searched by NCIt cancer code and GRCh38 genomic coordinates with DUP or DEL variant types.

Does OncoKB variant annotation require an API key?

Full OncoKB access requires setting the ONCOKB_API_TOKEN environment variable. Without it, OncoKB_annotate_variant runs in demo mode limited to BRAF, TP53, and ROS1 genes.

Why is my Progenetix CNV search returning no results?

Progenetix requires NCIt CURIE-format filters (e.g., NCIT:C4017), not free text, and GRCh38 1-based coordinates with a RefSeq accession like refseq:NC_000007.14. Use Progenetix_list_filtering_terms to confirm valid NCIt codes.

What are the limitations of TCGA survival analysis?

TCGA cohorts are retrospective and not treatment-stratified, so survival associations are hypothesis-generating. Small subgroups under 20 samples produce unreliable estimates, and GDC_get_survival only splits by single-gene mutation presence.