tcga-survival-for-gene
CommunityTCGA gene survival analysis in a single run.
AuthorMDhewei
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill enables researchers to quantify how a gene's expression relates to patient survival in TCGA cohorts by performing Kaplan-Meier analysis using live data from the GDC API.
Core Features & Use Cases
- Endpoint options: OS, DFS, or both, with flexible stratification (median, quartile, custom) across TCGA cohorts.
- Data fusion: resolves gene symbols via GDC, fetches clinical data and gene-expression values, merges them, and outputs per-case survival data and plots.
- Outputs: per-case survival table, KM plots (PNG/PDF), and a concise summary for reporting.
- Use case: assess whether high expression of a gene is associated with worse or better survival in a given TCGA cancer type.
Quick Start
Run the script with the gene symbol and cohort, select the endpoint(s), and specify an output directory to generate survival data and KM plots.
Dependency Matrix
Required Modules
lifelinesmatplotlibnumpypandasrequests
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: tcga-survival-for-gene Download link: https://github.com/MDhewei/bioinfor-claw/archive/main.zip#tcga-survival-for-gene Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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