The p-value only files are available in the “Public Dataset” tab.
To access the full data, please log into DSS and submit an application. Within the application, add this dataset (accession NG00126) in the “Choose a dataset” section. Once approved, you will be able to log in and access the data within the DARM portal.

Description

We performed Whole-exome and Whole-Genome association analyses with Alzheimer’s disease risk in ADSP data (NG00067.v5), focusing on non-Hispanic white individuals of European ancestry. Specifically, we designed novel variant filters that account for variant frequency differences across sequencing centers/platforms in the ADSP data. Here, we share the related summary statistics from the Alzheimer’s disease risk association analyses, together with those from the primary Fisher exact tests used to assess cross-center/platform variant frequency differences, as well as relevant information from other gnomAD filters and duplicate sample filters that were implemented. Technical and analytical details regarding the filters and association models are detailed in the manuscript. ADSP WES analyses included 11,573 individuals (5,418 controls and 6,155 cases). ADSP WGS analyses included 6,533 individuals (2,949 controls and 3,584 cases). The p-value data is generally available to all users using the public link. However, gaining access to the complete dataset requires a formal data request.

Available Filesets

NameAccessionLatest ReleaseDescription
Summary Statistics - Open Accessfsa000035NG00126.v1Public p-value only
Summary Statistics - Controlled Accessfsa000036NG00126.v1Full

View the File Manifest for a full list of files released in this dataset.

Consent LevelNumber of Subjects
DS-ADRD-IRB-PUB-NPUNA

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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 NG00126.

  • Belloy ME. A fast and robust strategy to remove variant levels artifacts in Alzheimer’s Disease Sequencing Project data. Neurol Genet. 2022 Aug. doi: 10.1212/NXG.0000000000200012 PubMed link