---
license: other
license_name: nih-genomic-data-sharing
license_link: https://gdc.cancer.gov/analyze-data/data-analysis-policies
pretty_name: TCGA Patients (Open Access)
tags:
  - cancer
  - tcga
  - clinical
  - genomics
configs:
  - config_name: TCGA-ACC
    data_files:
      - split: train
        path: TCGA-ACC/data.parquet
  - config_name: TCGA-BLCA
    data_files:
      - split: train
        path: TCGA-BLCA/data.parquet
  - config_name: TCGA-BRCA
    data_files:
      - split: train
        path: TCGA-BRCA/data.parquet
  - config_name: TCGA-CESC
    data_files:
      - split: train
        path: TCGA-CESC/data.parquet
  - config_name: TCGA-CHOL
    data_files:
      - split: train
        path: TCGA-CHOL/data.parquet
  - config_name: TCGA-COAD
    data_files:
      - split: train
        path: TCGA-COAD/data.parquet
  - config_name: TCGA-DLBC
    data_files:
      - split: train
        path: TCGA-DLBC/data.parquet
  - config_name: TCGA-ESCA
    data_files:
      - split: train
        path: TCGA-ESCA/data.parquet
  - config_name: TCGA-GBM
    data_files:
      - split: train
        path: TCGA-GBM/data.parquet
  - config_name: TCGA-HNSC
    data_files:
      - split: train
        path: TCGA-HNSC/data.parquet
  - config_name: TCGA-KICH
    data_files:
      - split: train
        path: TCGA-KICH/data.parquet
  - config_name: TCGA-KIRC
    data_files:
      - split: train
        path: TCGA-KIRC/data.parquet
  - config_name: TCGA-KIRP
    data_files:
      - split: train
        path: TCGA-KIRP/data.parquet
  - config_name: TCGA-LAML
    data_files:
      - split: train
        path: TCGA-LAML/data.parquet
  - config_name: TCGA-LGG
    data_files:
      - split: train
        path: TCGA-LGG/data.parquet
  - config_name: TCGA-LIHC
    data_files:
      - split: train
        path: TCGA-LIHC/data.parquet
  - config_name: TCGA-LUAD
    data_files:
      - split: train
        path: TCGA-LUAD/data.parquet
  - config_name: TCGA-LUSC
    data_files:
      - split: train
        path: TCGA-LUSC/data.parquet
  - config_name: TCGA-MESO
    data_files:
      - split: train
        path: TCGA-MESO/data.parquet
  - config_name: TCGA-OV
    data_files:
      - split: train
        path: TCGA-OV/data.parquet
  - config_name: TCGA-PAAD
    data_files:
      - split: train
        path: TCGA-PAAD/data.parquet
  - config_name: TCGA-PCPG
    data_files:
      - split: train
        path: TCGA-PCPG/data.parquet
  - config_name: TCGA-PRAD
    data_files:
      - split: train
        path: TCGA-PRAD/data.parquet
  - config_name: TCGA-READ
    data_files:
      - split: train
        path: TCGA-READ/data.parquet
  - config_name: TCGA-SARC
    data_files:
      - split: train
        path: TCGA-SARC/data.parquet
  - config_name: TCGA-SKCM
    data_files:
      - split: train
        path: TCGA-SKCM/data.parquet
  - config_name: TCGA-STAD
    data_files:
      - split: train
        path: TCGA-STAD/data.parquet
  - config_name: TCGA-TGCT
    data_files:
      - split: train
        path: TCGA-TGCT/data.parquet
  - config_name: TCGA-THCA
    data_files:
      - split: train
        path: TCGA-THCA/data.parquet
  - config_name: TCGA-THYM
    data_files:
      - split: train
        path: TCGA-THYM/data.parquet
  - config_name: TCGA-UCEC
    data_files:
      - split: train
        path: TCGA-UCEC/data.parquet
  - config_name: TCGA-UCS
    data_files:
      - split: train
        path: TCGA-UCS/data.parquet
  - config_name: TCGA-UVM
    data_files:
      - split: train
        path: TCGA-UVM/data.parquet
---

# TCGA Patients (Open Access)

Open-access TCGA data from the NCI Genomic Data Commons (GDC). Covers
all 33 TCGA projects.

**This view presents one HuggingFace subset per TCGA project**, with one row per patient. See the [`tcga-tabular-open`][tabular] companion for a per-table view of the same underlying data.

- **Generated:** 2026-05-09 22:03:39 UTC
- **Schema:** derived from the [GDC Data Dictionary][gdc-dict].
- **GDC data release:** Data Release 45.0 - December 04, 2025

## Data model

### Where the data comes from

Three sources feed each project's data, all open-access:

- **Case-level clinical structure** — fetched from the GDC `/cases`
  endpoint, returning the full nested case JSON (demographic + diagnoses
  → treatments + follow_ups + exposures + family_histories + samples →
  portions → analytes → aliquots). The biospecimen subtree on each case:

  ```
  case          one patient (TCGA-XX-1234)
  └── sample    physical specimen taken from the patient at one timepoint
                (Primary Tumor, Solid Tissue Normal, Blood Derived Normal, ...)
      └── portion    a piece of that sample for a specific lab process
          └── analyte    extracted material of one type (DNA or RNA)
              └── aliquot    a vial of that analyte handed off for sequencing
  ```

- **Per-modality molecular files** — discovered via `/files` (filtered
  by the clauses in the table below) and downloaded via `/data`. Each
  combination locks one `data_type` to a specific GDC pipeline so a
  future GDC addition can't quietly substitute a different pipeline
  under the same `data_type`.
- **BCR Clinical Supplement biotabs** — original Biospecimen Core
  Resource (BCR) clinical forms shipped as per-project TSVs (one per
  form: patient, follow_up, nte, drug, radiation, etc.). The harmonized
  `/cases` endpoint drops or under-populates a number of clinical fields
  the BCR-original biotabs preserve. The schema varies by cancer type
  (e.g. BLCA's BCG-response columns don't exist in CHOL's hepatic-marker
  forms), so each project's biotabs ship only the columns they actually
  carry. Discovered the same way (`/files` then `/data`) — see the
  filter table below.

### Source data filters (canonical)

Same in both views of the dataset; each row locks the `/files` query
for one source:

| data_type | data_format | data_category | experimental_strategy | analysis.workflow_type |
|---|---|---|---|---|
| `Masked Somatic Mutation` | `MAF` | `Simple Nucleotide Variation` | `WXS` | `Aliquot Ensemble Somatic Variant Merging and Masking` |
| `Gene Expression Quantification` | `TSV` | `Transcriptome Profiling` | `RNA-Seq` | `STAR - Counts` |
| `Clinical Supplement` | `bcr biotab` | `Clinical` | | |

### How each source appears in this view

| Source | Where it lands |
|---|---|
| GDC `/cases` | nested fields on each patient row (`demographic`, `diagnoses`, `follow_ups`, `exposures`, `family_histories`, `samples`); `gdc_portal_url` link added |
| Masked Somatic Mutation MAFs | `samples_masked_somatic_mutation` array on each patient row (sample FKs resolved alongside GDC's aliquot UUIDs) |
| Gene Expression Quantification | `samples_gene_expression_quantification` array on each patient row (`stranded_first` / `stranded_second` dropped — GDC harmonizes as unstranded) |
| BCR Clinical Supplements | `clinical_supplement` struct on each patient row, with sub-fields `patient` (1 dict) and `follow_ups` / `ntes` / `drugs` / `radiations` / `ablations` / `omfs` (lists of dicts). Sub-fields with no data for the project are omitted. |


### Specific to this view

- Convenience: each row carries `samples_<modality>` array columns so
  you can column-project just the molecular data you need without
  walking the nested GDC entities.
- Loading: the [`tcga2hf` package][repo] ships a typed `TcgaHfPatient`
  pydantic model that mirrors this schema and adds convenience joins
  (tumor/normal pairs, mutations-by-gene, expression-by-gene,
  longitudinal timeline).


### Provenance pinned per build

- `GET /status` → `data_release` / `tag` / `commit` saved in each
  project's `gdc_status.json`.
- `GET /v0/submission/_dictionary/_all` → schema dictionary snapshot
  saved alongside the raw data; its SHA-256 is recorded in
  `gdc_status.json`.

See the [repository][repo] for full request payloads, filter clauses,
and the build pipeline source.


## Survival endpoints (`survival_derived`)

We have provided a supplement to the GDC source data: re-derived
survival endpoints — Overall Survival (OS), Disease-Specific Survival
(DSS), Progression-Free Interval (PFI), Disease-Free Interval (DFI) —
following the algorithm published by **Liu et al. 2018**
([DOI 10.1016/j.cell.2018.02.052](https://doi.org/10.1016/j.cell.2018.02.052)).

Each patient row carries a top-level **`survival_derived` struct** with eight sub-fields: `os_event` / `os_time`, `dss_event` / `dss_time`, `pfi_event` / `pfi_time`, `dfi_event` / `dfi_time`. `*_event` is 0/1 (event observed vs censored); `*_time` is
days from `index_date` (TCGA: diagnosis date). DFI is null for SKCM /
THYM / UVM / LAML — Liu specifies no DFI for those tumor types.

We've reimplemented Liu's method against the current TCGA data and find
broad agreement with the original curated CDR. Differences exist and are
expected: this is a newer release of the underlying GDC data, so
re-curated clinical values, post-2018 patient additions, and schema
migrations all contribute to the gap. This work is evolving; see the
[repository][repo] for the full reproduction report and per-endpoint
methodology.

**Why we don't ship Liu's curated 2018 values directly:** the CDR is a
frozen 2018 snapshot derived from a since-modified GDC release.
Including those values would lock in irreproducible source-data drift.
We re-derive on every build, so the values reflect the current GDC and
are reproducible from this dataset's other tables alone.

## Loading

```python
from datasets import load_dataset

# One config per TCGA project.
luad = load_dataset("gabrielaltay/tcga-patients-open", "TCGA-LUAD")
```

Each row is one patient with the full GDC `case` structure nested
in-place plus the `survival_derived` struct.

## GDC references

- [Data dictionary][gdc-dict] (every entity + field definition)
- [Biospecimen Encyclopedia](https://docs.gdc.cancer.gov/Encyclopedia/pages/Biospecimen/)
- [MAF format spec](https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/)
- [Gene Expression Quantification spec](https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/)
- [Sample Type codes](https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/sample-type-codes)
- [TCGA Barcode reference](https://docs.gdc.cancer.gov/Encyclopedia/pages/TCGA_Barcode/)

## License & redistribution

Per the [NCI GDC Data Analysis Policy](https://gdc.cancer.gov/analyze-data/data-analysis-policies):

> The GDC itself places no restrictions (other than attempts at reidentification)
> on analysis or publication of open access data provided through the GDC Data Portal.

Per the [NCI TCGA citation page](https://www.cancer.gov/ccg/research/genome-sequencing/tcga/using-tcga-data/citing):

> Moratoria on all cancer types are now lifted and all TCGA data are available
> without restrictions on their use in publications or presentations.

Per the [GDC Data Access Processes and Tools page](https://gdc.cancer.gov/access-data/data-access-processes-and-tools):

> Open access data generally includes high level genomic data that is not
> individually identifiable, as well as most clinical and all biospecimen data
> elements.

## Restrictions on use

> Users of any data provided by GDC, whether open or controlled access, agree
> not to attempt to reidentify any individual participant in any study
> represented by GDC data, for any purpose whatever.
> ([source](https://gdc.cancer.gov/analyze-data/data-analysis-policies))

## Required acknowledgement

If you publish or present results derived from this dataset, include the
[NCI-required TCGA acknowledgement](https://www.cancer.gov/ccg/research/genome-sequencing/tcga/using-tcga-data/citing):

> The results <published or shown> here are in whole or part based upon data
> generated by the TCGA Research Network: https://www.cancer.gov/tcga.

Suggested citations:

- Grossman, R. L., et al. (2016). Toward a Shared Vision for Cancer Genomic Data.
  *NEJM*, 375(12), 1109-1112.
- The Cancer Genome Atlas Research Network. https://www.cancer.gov/tcga
- NCI Genomic Data Commons. https://gdc.cancer.gov

Policy references:
[GDC Policies](https://gdc.cancer.gov/about-gdc/gdc-policies),
[GDC Encyclopedia — Controlled Access][controlled] (defines what is *not* in this dataset),
[NIH Genomic Data Sharing Policy](https://sharing.nih.gov/genomic-data-sharing).

[controlled]: https://docs.gdc.cancer.gov/Encyclopedia/pages/Controlled_Access/

## Disclaimer

**This project is not affiliated with the NCI, GDC, or the TCGA Research
Network.** It is an experimental open-source pipeline that may change
significantly between versions. Pipeline source: [`galtay/tcga2hf`][repo].

[gdc-dict]: https://docs.gdc.cancer.gov/Data_Dictionary/
[repo]: https://github.com/galtay/tcga2hf
[patients]: https://huggingface.co/datasets/gabrielaltay/tcga-patients-open
[tabular]: https://huggingface.co/datasets/gabrielaltay/tcga-tabular-open