updating text of readme

README.md

@@ -297,10 +297,74 @@ configs:
 # Harbison 2004
 
 This Dataset is a parsed version of the data provided by Richard A. Young's lab at
-[their website](http://younglab.wi.mit.edu/regulatory_code). To cite
-this data, please use:  
+[their website](http://younglab.wi.mit.edu/regulatory_code). DOI and citation are in
+the dataset card above, or see the [ArrayExpress entry](https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-WMIT-10?query=%22richard%20young%22)
 
-[Harbison CT, Gordon DB, Lee TI, Rinaldi NJ, Macisaac KD, Danford TW, Hannett NM, Tagne
-JB, Reynolds DB, Yoo J, et al. 2004. Transcriptional regulatory code of a eukaryotic
-genome. Nature 431:
-99–104.doi:10.1038/nature02800](https://www.nature.com/articles/nature02800)
+## Accessing Data
+
+The examples below require
+[labretriever](https://github.com/cmatKhan/labretriever#installation)
+(`pip install labretriever`) and/or the
+[HuggingFace Hub client](https://huggingface.co/docs/huggingface_hub/installation)
+(`pip install huggingface_hub`).
+
+### Accessing Data with labretriever
+
+This repository is part of a collection configured as a unified database using
+[labretriever.VirtualDB](https://cmatkhan.github.io/labretriever/virtual_db_configuration/).
+Download the
+[collection config](https://github.com/BrentLab/tfbpshiny/blob/main/tfbpshiny/brentlab_yeast_collection.yaml)
+and use it to query the data directly in Python, or with an AI assistant using the
+[labretriever plugin](https://cmatkhan.github.io/labretriever/mcp_server/#quick-install-claude-code-plugin).
+
+```python
+from labretriever.virtual_db import VirtualDB
+from labretriever.datacard import DataCard
+
+# Citation and metadata
+card = DataCard("BrentLab/harbison_2004")
+info = card.info()
+print(info["doi"])
+print(info["citation"])
+
+# path to the downloaded brentlab_yeast_collection.yaml
+vdb = VirtualDB("/path/to/brentlab_yeast_collection.yaml")
+
+print(vdb.get_dataset_description("harbison"))
+vdb.query("SELECT * FROM harbison LIMIT 5")
+```
+
+### Direct parquet access
+
+The repository contains more data than what is exposed through the collection
+configuration. Use `DataCard.info()` to inspect available files, then download
+and query with DuckDB.
+
+Most files in this repository are single parquet files and can be read directly:
+
+```python
+from huggingface_hub import snapshot_download
+import duckdb
+
+repo_path = snapshot_download(
+    repo_id="BrentLab/harbison_2004",
+    repo_type="dataset",
+    allow_patterns="harbison_2004.parquet",
+)
+conn = duckdb.connect()
+# returns a pandas DataFrame with the first 5 rows
+conn.execute(
+    "SELECT * FROM read_parquet(?) LIMIT 5",
+    [f"{repo_path}/harbison_2004.parquet"],
+).df()
+```
+
+### Accessing using R
+
+Clone the repository and read parquet files directly with
+[arrow](https://arrow.apache.org/docs/r/):
+
+```r
+# install.packages("arrow")
+arrow::read_parquet("harbison_2004.parquet")
+```