| --- |
| language: en |
| license: mit |
| task_categories: |
| - tabular-classification |
| - feature-extraction |
| tags: |
| - bioinformatics |
| - cancer-research |
| - glioblastoma |
| - survival-prediction |
| - gene-expression |
| pretty_name: GBM Survival Gene Expression Dataset |
| size_categories: |
| - 1GB<n<10GB |
| --- |
| |
| # 🧬 GBM Survival Gene Expression Dataset |
|
|
| This dataset contains large-scale gene expression data (RNA-Seq and Microarray) curated for predicting the survival outcomes of patients with Glioblastoma Multiforme (GBM) and Lower-Grade Glioma (LGG). |
|
|
| It is specifically designed to be used with the [GBM Survival Mamba](https://github.com/congkx123789/Tin_sinh_h-c) project. |
|
|
| ## 📂 Data Structure |
|
|
| The data is organized into three main phases: |
|
|
| ### 1. `01_raw/` (Raw Data) |
| Untouched genomic data from international portals: |
| - **TCGA**: RNA-Seq data from The Cancer Genome Atlas (USA). |
| - **CGGA**: Chinese Glioma Genome Atlas data (Asia). |
| - **GEO**: Various cohorts from NCBI Gene Expression Omnibus (REMBRANDT, GSE4412, etc.). |
| |
| ### 2. `02_processed/` (Cleaned & Normalized) |
| Ready-to-use data for machine learning: |
| - **training/**: Internal Train/Val/Test splits used for model development. |
| - **validation/**: External independent cohorts for performance verification. |
| - Files include `X.csv` (feature matrices with 16,383 genes) and `y.csv` (survival time and status). |
|
|
| ### 3. `03_metadata/` |
| Mapping tables between Gene Symbols and Probe IDs, as well as clinical metadata. |
| |
| ## 🚀 How to use with the Project |
| |
| If you have cloned the [GitHub repository](https://github.com/congkx123789/Tin_sinh_h-c), you can automatically sync this data by running: |
| |
| ```bash |
| python scripts/download_data_hf.py |
| ``` |
| |
| This will download all files and place them in the correct `data/` directory structure. |
| |
| ## 📝 Data Sources & Citations |
| |
| If you use this data, please cite the original sources: |
| 1. TCGA Research Network: https://www.cancer.gov/tcga |
| 2. CGGA Database: http://www.cgga.org.cn/ |
| 3. NCBI GEO: https://www.ncbi.nlm.nih.gov/geo/ |
| |
| **Project Maintainer**: Cong, K. X. |
| |
