--- license: cc-by-4.0 task_categories: - tabular-regression - tabular-classification tags: - gwas - summary-statistics - psychiatric-genomics - pgc - adhd - mental-health - genetics - genomics - biology - health - bioinformatics pretty_name: PGC Attention Deficit Hyperactivity Disorder GWAS Summary Statistics size_categories: - 1M-10M configs: - config_name: adhd2010 default: true data_files: - split: train path: data/adhd2010/*.parquet - config_name: adhd2018_SexSpecific data_files: - split: train path: data/adhd2018_SexSpecific/*.parquet - config_name: adhd2019 data_files: - split: train path: data/adhd2019/*.parquet - config_name: adhd2022 data_files: - split: train path: data/adhd2022/*.parquet dataset_info: {} language: - en source_datasets: - pgc --- # PGC Attention Deficit Hyperactivity Disorder — GWAS Summary Statistics [![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey)](https://creativecommons.org/licenses/by/4.0/) ## Dataset Description Genome-wide association study (GWAS) summary statistics for **Attention Deficit Hyperactivity Disorder** phenotypes from the [Psychiatric Genomics Consortium (PGC)](https://pgc.unc.edu/). Each publication is available as a separate subset (config) and can be loaded independently. ## Usage ```python from datasets import load_dataset # Load a specific GWAS ds = load_dataset("OpenMed/pgc-adhd", "adhd2010") print(ds) ``` ### List all available subsets ```python from datasets import get_dataset_config_names print(get_dataset_config_names("OpenMed/pgc-adhd")) ``` ## Subsets | Config | Phenotype | Journal | Year | PubMed | Rows | |--------|-----------|---------|------|--------|------| | `adhd2010` | ADHD | JAACAP | 2010 | [20732625](https://pubmed.ncbi.nlm.nih.gov/20732625/) | — | | `adhd2018_SexSpecific` | ADHD (Sex-Specific) | Biological Psychiatry | 2018 | [29325848](https://pubmed.ncbi.nlm.nih.gov/29325848/) | — | | `adhd2019` | ADHD | Nature Genetics | 2019 | [30478444](https://pubmed.ncbi.nlm.nih.gov/30478444/) | — | | `adhd2022` | ADHD | Nature Genetics | 2022 | [36702997](https://pubmed.ncbi.nlm.nih.gov/36702997/) | — | ## Data Format All data is stored as **Apache Parquet** shards (10,000 rows each). Common columns: | Column | Description | |--------|-------------| | `SNP` / `ID` | SNP rsID or variant identifier | | `CHR` | Chromosome | | `BP` / `POS` | Base-pair position (typically GRCh37/hg19) | | `A1` | Effect allele | | `A2` | Non-effect allele | | `OR` / `BETA` | Odds ratio or effect size | | `SE` | Standard error | | `P` | P-value | | `_source_file` | Original source filename | > Column names vary between publications. Check each subset's schema. ## Citation Please cite the original publication (see PubMed links above) and acknowledge the PGC: > Data were obtained from the Psychiatric Genomics Consortium — https://pgc.unc.edu/ ## Terms of Use Released under **[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)**. - Cite the original publication(s) - Do not attempt to re-identify individual participants - Comply with the PGC [data use policies](https://pgc.unc.edu/for-researchers/data-access/) ## Source - [Psychiatric Genomics Consortium (PGC)](https://pgc.unc.edu/) - [PGC Downloads](https://pgc.unc.edu/for-researchers/download-results/) --- *Last updated: April 2026*