--- title: "NG00184 – ADSP FunGen xQTL Atlas" id: "9019" type: "dataset" slug: "ng00184" published_at: "2026-06-15T20:17:40+00:00" modified_at: "2026-09-02T19:42:29+00:00" url: "https://dss.niagads.org/datasets/ng00184/" markdown_url: "https://dss.niagads.org/datasets/ng00184.md" excerpt: "All data provided in this dataset are open access and are available publicly in the “Open Access Dataset” tab." taxonomy_dataset_categories: - "AD" - "Data Type" - "Disease" - "QTL Summary Statistics" --- ## Overview All data provided in this dataset are open access and are available publicly in the “Open Access Dataset” tab. #### Description This dataset contains brain quantitative trait locus (xQTL) summary statistics across six molecular phenotypes: expression quantitative trait loci (eQTL), histone acetylation quantitative trait loci (haQTL), DNA methylation quantitative trait loci (mQTL), protein quantitative trait loci (pQTL), splicing quantitative trait loci (sQTL), and single-nucleus expression quantitative trait loci (snuc-eQTL). The data were generated from four cohorts ([ROSMAP](https://dss.niagads.org/cohorts/religious-orders-study-memory-and-aging-project-rosmap/) , [MSBB](https://dss.niagads.org/cohorts/mount-sinai-brain-bank-msbb/) , [Knight-ADRC](https://dss.niagads.org/cohorts/knight-alzheimers-disease-research-center-kgad/) , [MiGA NBB](https://dss.niagads.org/cohorts/miga-nbb/) , [MiGA MSSM](https://dss.niagads.org/cohorts/miga-mssm/) ) and 20 brain cell types and regions, including microglia, monocytes, and multiple cortical areas. xQTLs were derived using a standardized Alzheimer’s Disease Sequencing Project Functional Genomics (ADSP FunGen-AD) pipeline with stringent quality control, followed by harmonization to a common set of genomic references to maximize accessibility and interoperability. Unlike previous xQTL resources, all summary statistics in this atlas provide consistent information on effect alleles, allele frequencies, and effect directions in uniform file formats, and include both full and significance-filtered result sets. This consistency is intended to remove common barriers to downstream applications such as colocalization, Mendelian randomization, and integrative fine-mapping, where heterogeneous formats and partial releases have been a major limitation. The atlas also extends cis-testing windows using brain topologically associating domains (TADs), yielding additional xQTLs beyond conventional fixed 1 megabase (Mb) windows and supporting more complete detection of regulatory variants. Variants and non-genic molecular features are annotated with overlapping or nearest genes to simplify gene-centric investigation. The ADSP Functional Genomics xQTL Atlas provides fully quality-controlled xQTL results, high-quality significant xQTL associations using Benjamini–Hochberg and Hierarchical Multiple Testing (HMT) adjustments, and single-context fine-mapping results generated via SuSiE and fSuSiE. All results are in standardized gzipped browser extensible data (BED–like) formats that are also browsable through the companion web portal at [https://xqtl.niagads.org/](https://xqtl.niagads.org/) . #### Available Filesets | Name | Accession | Latest Release | Description | | --- | --- | --- | --- | | ADSP FunGen xQTL Atlas (open access) | fsa000172 | NG00184.v1 | QTL Summary Statistics | View the [File Manifest](https://st1.niagads.org/portal/download-public/NG00184.v1/fm) for a full list of files released in this dataset. #### **ADSP FunGen xQTL Atlas Download Guide** xQTL Atlas files are not currently available as individual files, but instead as packaged .tar archives. Archives are named as: ADSP_FunGen_xQTL.v1...tar Example: ADSP_FunGen_xQTL.v1.pQTL.hmt_significant.tar | User goal | Recommended result type | Use case | | --- | --- | --- | | Start with high-confidence xQTL associations | hmt_significant | Best default choice for most users | | Use a broader significant association set | bh_significant | More inclusive than HMT; still FDR-filtered | | Access all tested associations | all | Complete summary statistics for custom analyses | | Prioritize likely causal variants | single_context_finemapping_cs95 | Fine-mapped variants in 95% credible sets | | Review all fine-mapping output | single_context_finemapping_all | Advanced fine-mapping analyses | **Choose the QTL type based on the molecular layer of interest:** | QTL type | Molecular layer | | --- | --- | | eQTL | Bulk gene expression | | snuc-eQTL | Cell-type-specific single-nucleus expression | | sQTL | Alternative splicing | | pQTL | Protein abundance | | mQTL | DNA methylation | | haQTL | H3K9ac histone acetylation | **Recommended starting point:** download .hmt_significant.tar for association results, or .single_context_finemapping_cs95.tar for fine-mapping results. Each .tar archive includes harmonized .bed.gz files, .bed.gz.tbi index files, metadata, and a manifest. ## Related Studies - [sa000078 - ADSP FunGen xQTL Atlas](https://dss.niagads.org/studies/sa000078/) This study constructs the largest brain-centric xQTL atlas to date, spanning five molecular phenotypes (expression, splicing, protein abundance, DNA methylation, histone acetylation) across 13 brain regions and 7 cell types… [Learn more](https://dss.niagads.org/studies/sa000078/) ## Acknowledgement ### Acknowledgment statement for any data distributed by NIAGADS: Data for this study were prepared, archived, and distributed by the National Institute on Aging Alzheimer's Disease Data Storage Site (NIAGADS) at the University of Pennsylvania (U24-AG041689), funded by the National Institute on Aging. Use the study-specific acknowledgement statements below (as applicable): ### For investigators using any data from this dataset: Please cite/reference the use of NIAGADS data by including the accession [NG00184](https://archive.niagads.org/datasets/NG00184) . ### For investigators using ADSP FunGen xQTL Atlas (sa000078) data: The data described here would not be possible without the participation of research volunteers and the contributions of collaborating investigators across multiple institutions. We gratefully acknowledge all researchers and staff involved in data generation, processing, and sharing. These data are made available as Open-Access. Individual-level human subject data are provided under Controlled Access and can be accessed at ng00067.v14, ng00105, ng00127, ng00083, ng00102, ng00104. Relevant support includes, but is not limited to, the following grants: NIH funding: R01AG076901, U01AG072572, RF1AG066107, R01AG067501, R01AG086467, U01AG072577, R01AG080810, U01AG058654, R35GM146868, U01AG058635, and support from the Freedom Together Foundation. ## Publications - Cifello Jeffrey. **A TAD-informed aging-brain xQTL atlas of multi-modal and cell-type-resolved regulatory variation***. 2026-6-1.*[DOI link](https://doi.org/https://doi.org/10.64898/2026.05.21.26353713) ### Total number of participants: 0 ## Source Datasets This dataset was generated using the following source dataset(s): - [NG00067 - Alzheimer's Disease Sequencing Project Umbrella Study](/datasets/ng00067)