feat(olink): greenfield NPX-style proteomics simulator

README.md

@@ -59,6 +59,35 @@ df = load_meds_events("~/.cache/synthlab/meds/synthea_100")
 
 Install the optional extra: `pip install synthlab[meds]`.
 
+### Olink NPX simulator (NEW)
+
+Simulate case/control Olink proteomics data with LOD-driven missingness
+and configurable group effects — the first greenfield open-source
+simulator targeted at Olink's NPX / PEA readout (existing tools like
+[MSstatsSampleSize](https://bioconductor.org/packages/MSstatsSampleSize/)
+target LC-MS/MS, and [OlinkAnalyze](https://github.com/Olink-Proteomics/OlinkRPackage)
+ships demo data but no simulator). Priors reflect UKB-PPP
+([Sun et al. 2023](https://www.nature.com/articles/s41586-023-06592-6))
+and OlinkAnalyze `npx_data1` / `npx_data2` baseline distributions:
+
+```python
+from synthlab import OlinkSimConfig, default_explore_3072_panel, simulate_olink_npx
+
+cfg = OlinkSimConfig(
+    n_samples=500,
+    panel=default_explore_3072_panel(),
+    group_effects={"CRP": {"case": 1.8}, "IL6": {"case": 1.2}},
+    group_assignments=["case"] * 250 + ["control"] * 250,
+    seed=42,
+)
+df = simulate_olink_npx(cfg)
+```
+
+See [`synthlab/olink.py`](synthlab/olink.py) for the full API
+(`OlinkPanelConfig`, `OlinkSimConfig`, `simulate_olink_npx`,
+`default_explore_3072_panel`, `write_olink_parquet`,
+`load_olink_parquet`).
+
 ## Installation
 
 ```bash

notebooks/README.md

@@ -0,0 +1,41 @@
+# SynthLab notebooks
+
+Demos and walkthroughs for the [SynthLab](https://github.com/bschilder/synthlab)
+synthetic-healthcare-data toolkit.
+
+## Index
+
+| Notebook | Module | Description |
+| -------- | ------ | ----------- |
+| [`olink_demo.ipynb`](olink_demo.ipynb) | [`synthlab.olink`](../synthlab/olink.py) | Olink NPX proteomics simulator — generate, analyse, visualise case vs control with LOD missingness + plate batch effects. |
+| [`Synthea.ipynb`](Synthea.ipynb) | [`synthlab.synthea`](../synthlab/synthea.py) | Run Synthea and convert CSV to OMOP. |
+| [`Coherent_MultimodalDataset.ipynb`](Coherent_MultimodalDataset.ipynb) | [`synthlab.coherent`](../synthlab/coherent.py) | Load and explore the Synthea Coherent multimodal dataset. |
+| [`Generate_MultimodalDataset.ipynb`](Generate_MultimodalDataset.ipynb) | [`synthlab.coherent`](../synthlab/coherent.py) | Generate multimodal synthetic cohorts. |
+| [`MedGemma_SOAP_Notes.ipynb`](MedGemma_SOAP_Notes.ipynb) | [`synthlab.soap`](../synthlab/soap.py) | MedGemma-based SOAP note generation with causal graph analysis. |
+| [`SNOMED_Entity_Linking.ipynb`](SNOMED_Entity_Linking.ipynb) | [`synthlab.snomed`](../synthlab/snomed.py) | SNOMED entity linking with SapBERT and FAISS. |
+| [`UKBiobank_Synthetic.ipynb`](UKBiobank_Synthetic.ipynb) | [`synthlab.download_ukbiobank_synthetic`](../synthlab/download_ukbiobank_synthetic.py) | Download and explore the UK Biobank Synthetic Dataset. |
+
+## Running the Olink demo
+
+The Olink NPX demo notebook needs the `viz` optional dependency group
+(`matplotlib`, `seaborn`, `scikit-learn`, `umap-learn`). Install alongside the
+core SynthLab package:
+
+```bash
+pip install 'synthlab[viz]'
+```
+
+Then open [`olink_demo.ipynb`](olink_demo.ipynb) in Jupyter — it runs
+end-to-end in under a minute on CPU with no external data dependencies.
+
+## Reproducing `olink_demo.ipynb`
+
+The notebook is assembled from
+[`_build_olink_demo.py`](_build_olink_demo.py) so the cell layout stays
+reviewable under version control. After editing the builder:
+
+```bash
+python notebooks/_build_olink_demo.py                             # rebuild cells
+jupyter nbconvert --to notebook --execute --inplace \\
+    notebooks/olink_demo.ipynb                                    # embed outputs
+```