| --- |
| license: cc0-1.0 |
| task_categories: |
| - tabular-classification |
| - feature-extraction |
| tags: |
| - tcga |
| - bulk-rna-seq |
| - methylation |
| - mutation |
| - cancer |
| - genomics |
| - multi-omics |
| pretty_name: TCGA PanCancer Atlas (8-subtype base set + per-architecture extensions) |
| --- |
| |
| # TCGA |
|
|
| A multi-omics subset of the TCGA PanCancer Atlas (RNA, methylation, mutation, clinical), |
| for use with [AUTOENCODIX](https://github.com/jan-forest/autoencodix_package) tutorials. |
|
|
| ## Base set (for `Vanillix` and other Tutorials) |
|
|
| Covers **8 cancer types**: BRCA, OV, LUAD, UCEC, LUSC, COAD, READ, UCS. |
|
|
| - `rna.parquet` — 3552 samples × 17448 genes (RNA expression) |
| - `methylation.parquet` — 3875 samples × 9829 genes (per-gene methylation) |
| - `mutation.parquet` — 3461 samples × 20304 genes (combined mutation/CNA score per gene; |
| restricted to samples that belong to the 8 cancer types above — the source file is a |
| pan-cancer TCGA mutation matrix, trimmed here to match this cohort) |
| - `clinical.parquet` — 3902 samples × 56 columns (sample-level clinical/annotation |
| metadata, incl. `CANCER_TYPE_ACRONYM`, `SUBTYPE`) |
|
|
| Gene identifiers are NCBI/Entrez gene IDs throughout, consistent with the ontology files |
| below. |
|
|
| ## `ontology/` — extension for `Ontix` Tutorial |
|
|
| Two ontology hierarchies, each as a 2-level gene-grouping file (gene ID → level-1 group, |
| level-1 group → level-2 group): |
|
|
| - `chromosome_ont_lvl1_ncbi.txt`, `chromosome_ont_lvl2.txt` — chromosome/cytoband-based |
| grouping |
| - `reactome_ont_lvl1.txt`, `reactome_ont_lvl2.txt` — Reactome pathway-based grouping |
| (level 2 uses human-readable Reactome pathway names) |
|
|
| ## `xmodalix/` — extension for `XModalix` Tutorial |
|
|
| Synthetic MNIST-style images paired to TCGA samples, one per sample, for the |
| image↔omics translation tutorial: |
|
|
| - `xmodalix/tcga_fake_images.zip` — 3907 grayscale 28×28 PNGs |
| - `xmodalix/tcga_image_mappings.txt` — tab-separated `sample_ids`, `img_paths`, |
| `extra_class_labels`, `CANCER_TYPE_ACRONYM`; 3230 of the 3902 base-set clinical |
| samples have a paired image (one image label per cancer type) |
|
|
| ## Loading |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| import pandas as pd |
| |
| rna_path = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="rna.parquet") |
| meth_path = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="methylation.parquet") |
| mut_path = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="mutation.parquet") |
| clin_path = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="clinical.parquet") |
| |
| rna = pd.read_parquet(rna_path) |
| ``` |
|
|
| Ontix additionally needs, e.g.: |
|
|
| ```python |
| chr1 = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="ontology/chromosome_ont_lvl1_ncbi.txt") |
| rea1 = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="ontology/reactome_ont_lvl1.txt") |
| ``` |
|
|
| XModalix additionally needs: |
|
|
| ```python |
| images_zip = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="xmodalix/tcga_fake_images.zip") |
| mapping = hf_hub_download(repo_id="autoencodix/tcga", repo_type="dataset", filename="xmodalix/tcga_image_mappings.txt") |
| ``` |
|
|
| ## License |
|
|
| **CC0 1.0 (Public Domain Dedication).** The TCGA PanCancer Atlas open-access data |
| (RNA, methylation, mutation, clinical) is designated public domain by the NIH Genomic |
| Data Commons, with no restrictions on reuse. The Reactome pathway groupings in |
| `ontology/` are separately licensed under CC0 by Reactome. The synthetic `xmodalix/` |
| images are generated by this project and released under the same CC0 terms. |
|
|
