introvoyz041/pgc-substance-use

--- 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*### 数据集元数据 - 许可证：CC BY 4.0 - 任务类别：表格回归（tabular regression）、表格分类（tabular classification） - 标签：全基因组关联研究（Genome-Wide Association Study, GWAS）、汇总统计量、精神基因组学、精神疾病基因组学联盟（Psychiatric Genomics Consortium, PGC）、物质使用障碍（Substance Use Disorders, SUD）、心理健康、遗传学、基因组学、生物学、健康、生物信息学 - 友好名称：PGC物质使用障碍全基因组关联研究汇总统计量（PGC Substance Use Disorders GWAS Summary Statistics） - 数据规模：100万-1000万条数据 - 配置项： 1. 配置名称：SUD2023，为默认配置，训练集数据路径：data/SUD2023/*.parquet 2. 配置名称：sud2018-alc，训练集数据路径：data/sud2018-alc/*.parquet 3. 配置名称：sud2019-alcuse，训练集数据路径：data/sud2019-alcuse/*.parquet 4. 配置名称：sud2020-cud，训练集数据路径：data/sud2020-cud/*.parquet 5. 配置名称：sud2020-op，训练集数据路径：data/sud2020-op/*.parquet - 语言：英语 - 源数据集：精神疾病基因组学联盟（PGC） # PGC物质使用障碍——全基因组关联研究汇总统计量 [](https://creativecommons.org/licenses/by/4.0/) ## 数据集说明 全基因组关联研究（Genome-Wide Association Study, GWAS）汇总统计量，对应来自[精神疾病基因组学联盟（Psychiatric Genomics Consortium, PGC）](https://pgc.unc.edu/)的**物质使用障碍（Substance Use Disorders, SUD）**表型数据。 本数据集将多篇GWAS研究成果作为独立的子集（配置项）进行组织，每个子集均可独立加载。 ## 使用方法 python from datasets import load_dataset # 加载指定的GWAS子集（例如SUD2023） ds = load_dataset("OpenMed/pgc-substance-use", "SUD2023") print(ds) ### 可用配置项 python from datasets import get_dataset_config_names configs = get_dataset_config_names("OpenMed/pgc-substance-use") print(configs) ## 子集（对应发表文献） | 配置名称 | 表型 | 期刊 | 发表年份 | PubMed编号 | 数据行数 | 许可证 | |--------|-----------|---------|------|--------|------|---------| | `SUD2023` | 物质使用障碍 | *Nature Mental Health* | 2023 | [37250466](https://pubmed.ncbi.nlm.nih.gov/37250466/) | 5,736,488 | CC BY 4.0 | | `sud2018-alc` | 酒精依赖 | *Nature Neuroscience* | 2018 | [30482948](https://pubmed.ncbi.nlm.nih.gov/30482948/) | — | CC BY 4.0 | | `sud2019-alcuse` | 酒精使用/AUDIT量表 | *American Journal of Psychiatry* | 2019 | [30336701](https://pubmed.ncbi.nlm.nih.gov/30336701/) | — | CC BY 4.0 | | `sud2020-cud` | 大麻使用障碍 | *Lancet Psychiatry* | 2020 | [33096046](https://pubmed.ncbi.nlm.nih.gov/33096046/) | — | CC BY 4.0 | | `sud2020-op` | 阿片类药物依赖 | *Molecular Psychiatry* | 2020 | [32099098](https://pubmed.ncbi.nlm.nih.gov/32099098/) | 57,445,238 | CC BY 4.0 | ## 数据格式 所有数据均已转换为**Apache Parquet**格式，每个数据分片包含10,000条记录。常见列字段如下： | 列名 | 说明 | |--------|-------------| | `SNP` / `ID` | SNP的rs编号或变异体标识符 | | `CHR` | 染色体编号 | | `BP` / `POS` | 碱基对位置（通常采用GRCh37/hg19参考基因组） | | `A1` / `ALT` | 效应等位基因 | | `A2` / `REF` | 非效应（参考）等位基因 | | `OR` / `BETA` | 比值比（OR）或效应量 | | `SE` | 标准误 | | `P` | P值 | | `INFO` | 填充质量得分 | | `FRQ` / `MAF` | 等位基因频率 | | `_source_file` | 该数据行对应的原始源文件名 | > **注意：** 不同研究的列名可能存在差异。`_source_file`字段可用于追踪每条数据行对应的原始源文件。 ## 引用规范 使用任一子集时，请引用以下内容： 1. 对应的**原始发表文献**（参见上文的PubMed链接） 2. Figshare平台上的**数据集DOI**（参见补充元数据） 3. **致谢精神疾病基因组学联盟：** > "Data were obtained from the Psychiatric Genomics Consortium — https://pgc.unc.edu/" ## 使用条款 本数据集采用**[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)**许可证进行发布。 使用本PGC汇总统计数据集即代表您同意遵守以下要求： 1. 引用相关原始发表文献 2. 不得尝试重新识别单个研究参与者 3. 遵守PGC的[数据使用政策](https://pgc.unc.edu/for-researchers/data-access/) ## 数据来源 - **联盟：** [精神疾病基因组学联盟（PGC）](https://pgc.unc.edu/) - **PGC下载页面：** [pgc.unc.edu/for-researchers/download-results/](https://pgc.unc.edu/for-researchers/download-results/) *最后更新：2026年4月*