Datasets:
Add clinical_supplement struct column to patient rows (BCR biotab data: patient/follow_ups/ntes/drugs/radiations/ablations/omfs sub-fields, per-project schema). Patients view now surfaces the same BCR data the tabular view exposes.
bbcc13a verified | 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 | |