Update TCGA patients (open access) dataset

README.md

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+---
+license: other
+license_name: nih-genomic-data-sharing
+license_link: https://gdc.cancer.gov/analyze-data/data-analysis-policies
+pretty_name: TCGA Patients (prototype)
+tags:
+  - cancer
+  - tcga
+  - clinical
+  - genomics
+configs:
+  - config_name: patients
+    data_files: patients/*.parquet
+---
+
+# TCGA Patients (prototype)
+
+One row per patient. Open-access TCGA clinical data from the NCI Genomic Data
+Commons (GDC), pre-joined into a single nested record per case so multi-modal
+oncology models can stream rich patient context in batches without doing joins.
+
+- **Projects included:** `TCGA-CHOL`, `TCGA-DLBC`
+- **Generated:** 2026-05-03 23:41:10 UTC
+- **Source:** NCI GDC `/cases` endpoint with expansions on `demographic`,
+  `diagnoses`, `diagnoses.treatments`, `follow_ups`, `exposures`,
+  `family_histories`, `project`.
+- **Access tier:** open. Redistributable; see [License & redistribution](#license--redistribution) below.
+- **Partitioning:** one Parquet file per TCGA project, at
+  `patients/<TCGA-XXXX>.parquet`. The `patients` HF config globs all of them.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+# Stream all projects (HF concatenates the per-project parquets):
+ds = load_dataset("<repo_id>", "patients", split="train", streaming=True)
+for patient in ds:
+    case_id = patient["case_id"]
+    diagnoses = patient["diagnoses"]                # list of dicts
+    treatments = [tx for dx in diagnoses for tx in dx["treatments"]]
+    ...
+
+# Restrict to one project: load only its parquet
+chol = load_dataset("<repo_id>", data_files="patients/TCGA-CHOL.parquet")
+```
+
+Or load into pyarrow / polars / pandas directly:
+
+```python
+import pyarrow.parquet as pq
+
+table = pq.read_table(
+    "patients/TCGA-CHOL.parquet",
+    columns=["case_id", "project_id", "demographic", "diagnoses"],
+)
+```
+
+## Verification
+
+This dataset's source is the NCI GDC. The same TCGA cases are also browsable on
+[cBioPortal](https://www.cbioportal.org/). cBioPortal hosts **multiple versions**
+of TCGA per disease (Firehose Legacy, PanCancer Atlas, GDC-sourced); the
+`*_tcga_gdc` family shares our upstream source and is the like-for-like
+comparison. Disease prefixes use cBioPortal's own taxonomy, not always the
+TCGA project suffix (e.g. `TCGA-DLBC` → `dlbclnos_tcga_gdc`).
+
+```
+https://www.cbioportal.org/patient/summary?studyId=<study>&caseId=<case_submitter_id>
+```
+
+For example, patient `TCGA-W5-AA39` (project `TCGA-CHOL`) →
+`https://www.cbioportal.org/patient/summary?studyId=chol_tcga_gdc&caseId=TCGA-W5-AA39`.
+
+## Schema
+
+```
+case_id: string
+case_submitter_id: string
+project_id: string
+primary_site: string
+disease_type: string
+demographic: struct<
+  demographic_id: string,
+  submitter_id: string,
+  gender: string,
+  sex_at_birth: string,
+  race: string,
+  ethnicity: string,
+  vital_status: string,
+  age_at_index: int64,
+  days_to_birth: int64,
+  days_to_death: int64,
+  year_of_birth: int64,
+  year_of_death: int64,
+  country_of_residence_at_enrollment: string,
+>
+diagnoses: list<struct<
+  diagnosis_id: string,
+  submitter_id: string,
+  primary_diagnosis: string,
+  morphology: string,
+  tissue_or_organ_of_origin: string,
+  site_of_resection_or_biopsy: string,
+  icd_10_code: string,
+  ajcc_pathologic_stage: string,
+  ajcc_pathologic_t: string,
+  ajcc_pathologic_n: string,
+  ajcc_pathologic_m: string,
+  ajcc_staging_system_edition: string,
+  age_at_diagnosis: int64,
+  days_to_diagnosis: double,
+  year_of_diagnosis: int64,
+  prior_malignancy: string,
+  prior_treatment: string,
+  synchronous_malignancy: string,
+  classification_of_tumor: string,
+  last_known_disease_status: string,
+  days_to_last_follow_up: double,
+  days_to_last_known_disease_status: double,
+  days_to_recurrence: double,
+  residual_disease: string,
+  diagnosis_is_primary_disease: bool,
+  treatments: list<struct<
+    treatment_id: string,
+    submitter_id: string,
+    treatment_type: string,
+    treatment_or_therapy: string,
+    treatment_intent_type: string,
+    treatment_outcome: string,
+    therapeutic_agents: string,
+    days_to_treatment_start: double,
+    days_to_treatment_end: double,
+    initial_disease_status: string,
+  >>,
+>>
+follow_ups: list<struct<
+  follow_up_id: string,
+  submitter_id: string,
+  timepoint_category: string,
+  disease_response: string,
+  progression_or_recurrence: string,
+  days_to_follow_up: double,
+  days_to_progression: double,
+  days_to_recurrence: double,
+  ecog_performance_status: string,
+>>
+exposures: list<struct<
+  exposure_id: string,
+  submitter_id: string,
+  tobacco_smoking_status: string,
+  cigarettes_per_day: double,
+  years_smoked: double,
+  alcohol_history: string,
+  alcohol_intensity: string,
+  bmi: double,
+  weight: double,
+  height: double,
+>>
+family_histories: list<struct<
+  family_history_id: string,
+  submitter_id: string,
+  relationship_type: string,
+  relative_with_cancer_history: string,
+  relationship_primary_diagnosis: string,
+>>
+```
+
+Notes on the nested layout:
+
+- `demographic` is a single `struct` (1:1 with the patient).
+- `diagnoses`, `follow_ups`, `exposures`, `family_histories` are `list<struct<...>>`
+  (0..N per patient).
+- `treatments` is nested *inside* each diagnosis (`diagnoses[i].treatments`), so
+  the source 1:N relationship between diagnosis and treatment is preserved.
+- All leaf fields are nullable.
+
+## License & redistribution
+
+This dataset only contains TCGA data fetched from the GDC's **open-access** tier
+(`/cases` endpoint with `access=open`). 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.
+
+The clinical data here is squarely within that scope.
+
+## Restrictions on use
+
+The single hard restriction inherited from the GDC policy applies to all
+downstream users:
+
+> 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, please 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 for the GDC and TCGA:
+
+- 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
+
+Additional policy references:
+
+- [GDC Policies (umbrella)](https://gdc.cancer.gov/about-gdc/gdc-policies)
+- [GDC Encyclopedia — Controlled Access](https://docs.gdc.cancer.gov/Encyclopedia/pages/Controlled_Access/) (defines what is *not* in this dataset)
+- [NIH Genomic Data Sharing Policy](https://sharing.nih.gov/genomic-data-sharing)
+
+## Disclaimer
+
+Prototype dataset for engineering validation. Schemas, projects, and column
+coverage will change as additional modalities (mutations, expression, copy number)
+are added — likely as additional top-level nested columns on the same patient row.
+Re-derive from the GDC for any analysis where freshness matters.

patients/TCGA-CHOL.parquet

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patients/TCGA-DLBC.parquet

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