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license: cc-by-4.0
task_categories:
- tabular-regression
- tabular-classification
tags:
- gwas
- summary-statistics
- psychiatric-genomics
- pgc
- sud
- mental-health
- genetics
- genomics
- biology
- health
- bioinformatics
pretty_name: PGC Substance Use Disorders GWAS Summary Statistics
size_categories:
- 1M-10M
configs:
- config_name: SUD2023
default: true
data_files:
- split: train
path: data/SUD2023/*.parquet
- config_name: sud2018-alc
data_files:
- split: train
path: data/sud2018-alc/*.parquet
- config_name: sud2019-alcuse
data_files:
- split: train
path: data/sud2019-alcuse/*.parquet
- config_name: sud2020-cud
data_files:
- split: train
path: data/sud2020-cud/*.parquet
- config_name: sud2020-op
data_files:
- split: train
path: data/sud2020-op/*.parquet
language:
- en
source_datasets:
- pgc
---
# PGC Substance Use Disorders — GWAS Summary Statistics
[](https://creativecommons.org/licenses/by/4.0/)
## Dataset Description
Genome-wide association study (GWAS) summary statistics for **Substance Use Disorders** phenotypes from the [Psychiatric Genomics Consortium (PGC)](https://pgc.unc.edu/).
This dataset contains multiple GWAS publications as separate subsets (configs). Each can be loaded independently.
## Usage
```python
from datasets import load_dataset
# Load a specific GWAS (e.g., SUD2023)
ds = load_dataset("OpenMed/pgc-substance-use", "SUD2023")
print(ds)
```
### Available Configs
```python
from datasets import get_dataset_config_names
configs = get_dataset_config_names("OpenMed/pgc-substance-use")
print(configs)
```
## Subsets (Publications)
| Config | Phenotype | Journal | Year | PubMed | Rows | License |
|--------|-----------|---------|------|--------|------|---------|
| `SUD2023` | Substance Use Disorder | Nature Mental Health | 2023 | [37250466](https://pubmed.ncbi.nlm.nih.gov/37250466/) | 5,736,488 | CC BY 4.0 |
| `sud2018-alc` | Alcohol Dependence | Nature Neuroscience | 2018 | [30482948](https://pubmed.ncbi.nlm.nih.gov/30482948/) | — | CC BY 4.0 |
| `sud2019-alcuse` | Alcohol Use / AUDIT | American Journal of Psychiatry | 2019 | [30336701](https://pubmed.ncbi.nlm.nih.gov/30336701/) | — | CC BY 4.0 |
| `sud2020-cud` | Cannabis Use Disorder | Lancet Psychiatry | 2020 | [33096046](https://pubmed.ncbi.nlm.nih.gov/33096046/) | — | CC BY 4.0 |
| `sud2020-op` | Opioid Dependence | Molecular Psychiatry | 2020 | [32099098](https://pubmed.ncbi.nlm.nih.gov/32099098/) | 57,445,238 | CC BY 4.0 |
## Data Format
All data has been converted to **Apache Parquet** format with shards of 10,000 rows. Common columns include:
| Column | Description |
|--------|-------------|
| `SNP` / `ID` | SNP rsID or variant identifier |
| `CHR` | Chromosome |
| `BP` / `POS` | Base-pair position (typically GRCh37/hg19) |
| `A1` / `ALT` | Effect allele |
| `A2` / `REF` | Non-effect (reference) allele |
| `OR` / `BETA` | Odds ratio or effect size |
| `SE` | Standard error |
| `P` | P-value |
| `INFO` | Imputation quality score |
| `FRQ` / `MAF` | Allele frequency |
| `_source_file` | Original source filename |
> **Note:** Column names vary between publications. The `_source_file` column tracks the original file each row came from.
## Citation
When using any subset, please cite:
1. The **original publication** (see PubMed links above)
2. The **data DOI** from Figshare (see supplementary metadata)
3. **Acknowledge the PGC:**
> "Data were obtained from the Psychiatric Genomics Consortium — https://pgc.unc.edu/"
## Terms of Use
This dataset is released under the **[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)** license.
By using PGC summary statistics you agree to:
1. Cite the original publication(s)
2. Not attempt to re-identify individual participants
3. Comply with the PGC's [data use policies](https://pgc.unc.edu/for-researchers/data-access/)
## Source
- **Consortium:** [Psychiatric Genomics Consortium (PGC)](https://pgc.unc.edu/)
- **PGC Downloads:** [pgc.unc.edu/for-researchers/download-results/](https://pgc.unc.edu/for-researchers/download-results/)
---
*Last updated: April 2026*
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