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curatedTCGAData-mcp

Access TCGA cancer genomics data and build MultiAssayExperiment objects in R.

Updated Nov 3, 2025
Search Tags:#data access#cancer genomics#mutations#bioconductor#rna-seq#tcga#multi-omic
One-click install
npx skills add https://github.com/vjcitn/BiocMCP-tcga --skill curatedtcgadata-mcp
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: curatedTCGAData-mcp
Source: https://github.com/vjcitn/BiocMCP-tcga/tree/main
Command: npx skills add https://github.com/vjcitn/BiocMCP-tcga --skill curatedtcgadata-mcp

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires curatedTCGAData, MultiAssayExperiment, TCGAutils, SummarizedExperiment, RaggedExperiment, S4Vectors, methods, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies the complex process of accessing and preparing The Cancer Genome Atlas (TCGA) data for analysis, making multi-omic cancer research more accessible.

Core Features & Use Cases

  • Discover Data: Easily list available cancer types and the specific data assays (e.g., RNA-seq, mutations, copy number) for each.
  • Build Datasets: Create MultiAssayExperiment objects, which integrate various data types for a given cancer or multiple cancers.
  • Data Filtering & Preparation: Filter data to include only primary tumors and extract essential clinical or subtype information.
  • Use Case: A researcher wants to investigate gene expression differences between primary tumors and normal tissue for a specific cancer. They can use this Skill to find available RNA-seq data, build a dataset, filter for primary tumors, and extract the relevant expression matrix.

Quick Start

List all available TCGA cancer types.

Frequently Asked Questions about curatedTCGAData-mcp

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

FAQPage Schema
How do I access TCGA cancer genomics data in R for multi-omic analysis?▼

Access TCGA cancer genomics data in R by using the curatedTCGAData Bioconductor package to discover available cancer types, build integrated MultiAssayExperiment objects, and prepare datasets for multi-omic analysis.

What TCGA data assays are available for cancer research through Bioconductor?▼

Available TCGA data assays include RNA-seq, mutations, and copy number variations. You can easily list specific data assays available for each cancer type to determine what multi-omic data is accessible for your research.

How do I filter TCGA data to include only primary tumors and extract clinical information?▼

Filter TCGA data to include only primary tumors and extract clinical information by using the data preparation features to subset your MultiAssayExperiment object and isolate the relevant clinical or subtype variables.

Can I integrate multiple data types when analyzing TCGA cancer data?▼

Yes, you can integrate multiple data types when analyzing TCGA cancer data by building MultiAssayExperiment objects, which combine various data assays like RNA-seq and mutations for a given cancer into a single integrated dataset.

Do I need an R programming environment to use curatedTCGAData for cancer research?▼

Yes, you need an R programming environment because the Skill integrates with Bioconductor workflows and relies on R packages like MultiAssayExperiment, SummarizedExperiment, and RaggedExperiment to manage and process the data.

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