Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,253 @@
+---
+language:
+- en
+tags:
+- pathology
+- histology
+- tumor-grade
+- histologic-type
+- lymphovascular-invasion
+- necrosis
+- tils
+- breast-cancer
+- sub-saharan-africa
+license: cc-by-nc-4.0
+pretty_name: SSA Breast Pathology & Histology Dataset (Women, Multi-ancestry)
+task_categories:
+- other
+size_categories:
+- 1K<n<10K
+---
+
+# SSA Breast Pathology & Histology Dataset (Women, Multi-ancestry, Synthetic)
+
+## Dataset summary
+
+This dataset provides a **synthetic cohort of invasive breast cancers** in women across multiple ancestry groups, with emphasis on **sub-Saharan Africa (SSA)** and comparable reference populations.
+
+Pathology features include:
+
+- **Tumor grade** (Nottingham-like grades G1–G3).
+- **Histologic type** (NST/ductal, lobular, medullary-like, mucinous, other special types).
+- **Lymphovascular invasion (LVI)**.
+- **Necrosis patterns** (none, focal, extensive).
+- **Tumor-infiltrating lymphocytes (TILs)** category (low, intermediate, high).
+
+Distributions are anchored qualitatively to SEER-based histology series, Nottingham grade cohorts, LVI reviews, necrosis descriptions, and TNBC TIL literature, but all tumors are fully synthetic.
+
+
+## Cohort design
+
+### Sample size and populations
+
+- **Total N**: 10,000 synthetic invasive breast cancers.
+- **Populations**:
+  - `SSA_West`: 2,000
+  - `SSA_East`: 2,000
+  - `SSA_Central`: 1,500
+  - `SSA_Southern`: 1,500
+  - `AAW` (African American women): 1,500
+  - `EUR` (European reference): 1,000
+  - `EAS` (East Asian reference): 500
+
+- **Sex**:
+  - Predominantly `Female`, with a small fraction of male breast cancers (`~1%`).
+
+- **Age**:
+  - 18–90 years.
+  - Older mean age at diagnosis in reference populations (EUR/EAS/AAW) relative to SSA clusters.
+
+
+## Pathology variables
+
+### Tumor grade (Nottingham-like)
+
+Variable:
+
+- `tumor_grade` – one of:
+  - `G1` – low grade.
+  - `G2` – intermediate grade.
+  - `G3` – high grade.
+
+Distributions by population approximate published Nottingham histologic grade series:
+
+- Typical ranges of **~15–25% G1**, **~40–50% G2**, **~30–40% G3**.
+- SSA and AAW populations have **somewhat higher G3 fractions**, reflecting higher prevalence of aggressive subtypes such as TNBC.
+- EUR/EAS reference groups have relatively higher G1 and lower G3 proportions.
+
+
+### Histologic type
+
+Variable:
+
+- `histologic_type` – one of:
+  - `NST_ductal` – invasive carcinoma of no special type (ductal/NST).
+  - `Lobular` – invasive lobular carcinoma.
+  - `Medullary_like` – medullary or medullary-like carcinomas.
+  - `Mucinous` – mucinous/colloid carcinomas.
+  - `Other_special` – other special histologic types grouped.
+
+Anchored to SEER and WHO-based estimates:
+
+- **NST/ductal**: ~75–80% of invasive cases.
+- **Lobular**: ~8–12% (slightly more common in some EUR/EAS cohorts).
+- Remaining **medullary-like, mucinous, and other special types** together account for ~10–15%.
+
+
+### Lymphovascular invasion (LVI)
+
+Variable:
+
+- `lvi_status` – `Absent` or `Present`.
+- Derived flag: `lvi_present` (True if `Present`).
+
+Modeled prevalence is based on LVI reviews (typically **15–35%** in invasive breast cancer):
+
+- Lower LVI prevalence in **G1** tumors (~5–10%).
+- Intermediate in **G2** (~15–25%).
+- Higher in **G3** (~30–40%), with modest variation by population.
+
+
+### Necrosis patterns
+
+Variable:
+
+- `necrosis_pattern` – one of:
+  - `None`
+  - `Focal`
+  - `Extensive`
+- Derived flag: `necrosis_any` (True if `Focal` or `Extensive`).
+
+Patterns align with descriptions of necrosis in high-grade DCIS and invasive tumors:
+
+- **G1**: mostly `None` with occasional `Focal` necrosis; `Extensive` rare.
+- **G2**: increased `Focal` and some `Extensive` necrosis.
+- **G3**: highest proportion of `Extensive` necrosis (e.g., comedo/central necrosis), plus substantial `Focal` necrosis.
+
+
+### Tumor-infiltrating lymphocytes (TILs)
+
+Variable:
+
+- `tils_category` – one of:
+  - `Low`
+  - `Intermediate`
+  - `High`
+- Derived flag: `tils_high` (True if `High`).
+
+Informed by TIL consensus papers and TNBC cohorts:
+
+- **TNBC-enriched populations (e.g., some SSA and AAW groups)** are modeled with **higher fractions of `High` TILs** (~20–24%) and substantial `Intermediate` TILs.
+- **EUR/EAS** cohorts have more `Low` TILs and fewer `High` TILs, reflecting higher ER+/HER2− prevalence and lower immunogenicity.
+
+
+## File and schema
+
+### `pathology_histology_data.parquet` / `pathology_histology_data.csv`
+
+Each row represents an invasive breast cancer case:
+
+- **Demographics**
+  - `sample_id`
+  - `population`
+  - `region`
+  - `is_SSA`
+  - `is_reference_panel`
+  - `sex`
+  - `age`
+
+- **Primary pathology features**
+  - `tumor_grade` (G1, G2, G3)
+  - `histologic_type`
+  - `lvi_status`
+  - `necrosis_pattern`
+  - `tils_category`
+
+- **Derived indicators**
+  - `lvi_present`
+  - `necrosis_any`
+  - `tils_high`
+
+
+## Generation
+
+The dataset is generated using:
+
+- `pathology_histology/scripts/generate_pathology_histology.py`
+
+with configuration in:
+
+- `pathology_histology/configs/pathology_histology_config.yaml`
+
+and literature inventory in:
+
+- `pathology_histology/docs/LITERATURE_INVENTORY.csv`
+
+Key steps:
+
+1. **Cohort construction** – multi-ancestry invasive cancer cohort with age and sex distributions by population.
+2. **Tumor grade assignment** – sample `tumor_grade` by population according to Nottingham-like distributions.
+3. **Histologic type assignment** – sample `histologic_type` by population, with NST/ductal as the dominant category.
+4. **LVI and necrosis assignment** – sample `lvi_status` and `necrosis_pattern` conditional on population and `tumor_grade`, with higher LVI and necrosis rates in high-grade tumors.
+5. **TILs assignment** – sample `tils_category` by population, reflecting higher immunogenicity/high-TIL fractions in some SSA and TNBC-enriched groups.
+
+
+## Validation
+
+Validation is performed with:
+
+- `pathology_histology/scripts/validate_pathology_histology.py`
+
+and summarized in:
+
+- `pathology_histology/output/validation_report.md`
+
+Checks include:
+
+- **C01–C02** – Sample size and population counts vs config.
+- **C03** – Tumor grade distributions by population.
+- **C04** – Histologic type distributions by population.
+- **C05** – LVI distributions by population and grade.
+- **C06** – Necrosis pattern distributions by population and grade.
+- **C07** – TIL category distributions by population.
+- **C08** – Missingness in key variables.
+
+The released version passes all checks within the configured tolerance, yielding an **overall validation status of `PASS`**.
+
+
+## Intended use
+
+This dataset is intended for:
+
+- **Pathology-centric modeling** of tumor aggressiveness and microenvironment across ancestries.
+- **Integration** with other Electric Sheep Africa synthetic datasets (e.g., genomics, comorbidities, environmental exposures) to build multi-modal cancer models.
+- **Educational use** for understanding relationships between grade, histologic type, LVI, necrosis, and TILs.
+
+It is **not suitable** for:
+
+- Estimating true prevalence of grades or histologies in any specific registry or country.
+- Direct clinical decision-making or quality benchmarking.
+
+All tumors are synthetic and non-identifiable.
+
+
+## Ethical considerations
+
+- No patient-level data are used; all records are simulated.
+- Population differences in grade, histology, LVI, or TILs are modeled for methodological realism and should not be used to stigmatize groups.
+- Analyses should be contextualized with up-to-date cancer registry and pathology data.
+
+
+## License
+
+- License: **CC BY-NC 4.0**.
+- Free for non-commercial research, education, and methods development with attribution.
+
+
+## Citation
+
+If you use this dataset, please cite:
+
+> Electric Sheep Africa. "SSA Breast Pathology & Histology Dataset (Women, Multi-ancestry, Synthetic)." Hugging Face Datasets.
+
+and, as appropriate, key pathology literature on histologic types, Nottingham grade, LVI, necrosis, and TILs in breast cancer.