---
title: "Legacy Datasets Moving to DSS"
id: "7683"
type: "page"
slug: "legacy-datasets-moving-to-dss"
published_at: "2025-01-21T20:22:17+00:00"
modified_at: "2025-01-22T20:49:39+00:00"
url: "https://dss.niagads.org/legacy-datasets-moving-to-dss/"
markdown_url: "https://dss.niagads.org/legacy-datasets-moving-to-dss.md"
excerpt: "Notice: Dataset Migration to DSS These datasets are temporarily unavailable as we transition them to the NIAGADS Data Sharing Service (DSS) to comply with new security standards for genomic data repositories. We appreciate your patience during this process. For more..."
---

**Notice: Dataset Migration to DSS**

These datasets are temporarily unavailable as we transition them to the NIAGADS Data Sharing Service (DSS) to comply with new security standards for genomic data repositories. We appreciate your patience during this process.

For more details about the legacy dataset migration, please visit our [FAQ page](https://niagads.scrollhelp.site/support/legacy-dataset-migration-to-dss)
. If you need access to this dataset sooner, you can request prioritization by submitting a ticket through our [support system](mailto:help@niagads.org?subject=Legacy%20Dataset%20Request)
.

Thank you for your understanding.

- [NG00010 – Caribbean Hispanic AD Study](https://dss.niagads.org/datasets/ng00010/)
- [NG00015 – Genetics Consortium for Late Onset of Alzheimers](https://dss.niagads.org/datasets/ng00015/)
- [NG00017 – OHSU GWAS](https://dss.niagads.org/datasets/ng00017/)
- [NG00025 – eGWAS Mayo](https://dss.niagads.org/datasets/ng00025/)
- [NG00026 – University of Pittsburgh GWAS](https://dss.niagads.org/datasets/ng00026/)
- [NG00027 – ADGC Summary Statistics – Naj et al. (2011)](https://dss.niagads.org/datasets/ng00027/)
- [NG00028 – TGEN II GWAS](https://dss.niagads.org/datasets/ng00028/)
- [NG00031 – MIRAGE NHW GWAS](https://dss.niagads.org/datasets/ng00031/)
- [NG00032 – NIA-LOAD (ADGC subset) GWAS](https://dss.niagads.org/datasets/ng00032/)
- [NG00033 – Identifying Rare Variants That Increase Risk For Alzheimer’s Disease](https://dss.niagads.org/datasets/ng00033/)
- [NG00034 – ACT and Genetic Differences GWAS](https://dss.niagads.org/datasets/ng00034/)
- [NG00036 – IGAP Summary Statistics – Lambert et al. (2013)](https://dss.niagads.org/datasets/ng00036/)
- [NG00037 – Progressive Supranuclear Palsy (PSP) GWAS](https://dss.niagads.org/datasets/ng00037/)
- [NG00038 – Expression Levels from AD Case-Control Study](https://dss.niagads.org/datasets/ng00038/)
- [NG00039 – ADGC African American Summary Statistics – Reitz et al. (2013)](https://dss.niagads.org/datasets/ng00039/)
- [NG00040 – Multi-Ethnic Exome Array Study of AD, FTD, and PSP](https://dss.niagads.org/datasets/ng00040/)
- [NG00041 – ADGC Neuropath Summary Stats and Phenotypes – Beecham et al. (2014)](https://dss.niagads.org/datasets/ng00041/)
- [NG00042 – Miami, Vanderbilt, and Medical School of Mount Sinai (UMVUMSSM) GWAS](https://dss.niagads.org/datasets/ng00042/)
- [NG00043 – MAYO GWAS](https://dss.niagads.org/datasets/ng00043/)
- [NG00045 – Progressive Supranuclear Palsy (PSP) Summary Statistics – Hoglinger et al. (2011)](https://dss.niagads.org/datasets/ng00045/)
- [NG00047 – Indianapolis African American GWAS](https://dss.niagads.org/datasets/ng00047/)
- [NG00048 – ADGC Age at Onset Summary Statistics – Naj et al. (2014)](https://dss.niagads.org/datasets/ng00048/)
- [NG00051 – SORL1 coding variants and risk for AD](https://dss.niagads.org/datasets/ng00051/)
- [NG00053 – IGAP Summary Statistics, ADGC subset – Lambert et al. (2013)](https://dss.niagads.org/datasets/ng00053/)
- [NG00055 – CSF Aβ/ptau Summary Statistics – Deming Y et al. (2017)](https://dss.niagads.org/datasets/ng00055/)
- [NG00056 – Transethnic GWAS Summary Statistics – Jun et al. (2017)](https://dss.niagads.org/datasets/ng00056/)
- [NG00057 – Laser Capture and RNA sequencing of Microglia in human brain – Mastroeni et al.(2017)](https://dss.niagads.org/datasets/ng00057/)
- [NG00061 – Functional Annotation of genomic variants in studies of LOAD](https://dss.niagads.org/datasets/ng00061/)
- [NG00062 – Episodic Memory Trajectories (EMTs) of 13,037 elderly](https://dss.niagads.org/datasets/ng00062/)
- [NG00063 – Prediction of Psychosis in Alzheimer Disease](https://dss.niagads.org/datasets/ng00063/)
- [NG00065 – ADSP Discovery Case/Control Association Results](https://dss.niagads.org/datasets/ng00065/)
- [NG00072 – NLTCS (The National Long Term Care Survey) SNP DATA I](https://dss.niagads.org/datasets/ng00072/)
- [NG00073 – Genome-wide summary statistics for cognitively defined late-onset Alzheimer’s disease subgroups](https://dss.niagads.org/datasets/ng00073/)
- [NG00074 – Multi-cohort study of endo-lysosomal system genetics and dementia](https://dss.niagads.org/datasets/ng00074/)
- [NG00076 – ADGC case-control summary statistics on 7050 samples not included in the IGAP-2013 discovery stage](https://dss.niagads.org/datasets/ng00076/)
- [NG00077 – Genetic analyses of patients with CTE](https://dss.niagads.org/datasets/ng00077/)
- [NG00078 – IGAP APOE-Stratified Analysis Summary Statistics – Jun et al. (2015)](https://dss.niagads.org/datasets/ng00078/)
- [NG00079 – Northshore Exome Chip](https://dss.niagads.org/datasets/ng00079/)
- [NG00080 – Miami Exome Chip](https://dss.niagads.org/datasets/ng00080/)
- [NG00081 – CHOP Exome Chip](https://dss.niagads.org/datasets/ng00081/)
- [NG00083 – Circular RNAs in Alzheimer Disease Brains – RNA-seq Data](https://dss.niagads.org/datasets/ng00083/)
- [NG00084 – Immune-related genetic enrichment in FTD summary statistics – Broce et al. 2018](https://dss.niagads.org/datasets/ng00084/)
- [NG00085 – ExomeChip – WashU](https://dss.niagads.org/datasets/ng00085/)
- [NG00086 – NACC Polygenic Hazard Score](https://dss.niagads.org/datasets/ng00086/)
- [NG00088 – GWAS Summary Statistics of informed conditioning analysis in African Americans](https://dss.niagads.org/datasets/ng00088/)
- [NG00089 – CSF TREM2 Summary Statistics](https://dss.niagads.org/datasets/ng00089/)
- [NG00091 – Results of gene-based weighted burden analyses using SCOREASSOC and GENEVARASSOC applied to the ADSP discovery sample](https://dss.niagads.org/datasets/ng00091/)
- [NG00096 – MTC GWAS (CHOP)](https://dss.niagads.org/datasets/ng00096/)
- [NG00097 – TARCC GWAS](https://dss.niagads.org/datasets/ng00097/)
- [NG00098 – Case of CBD for determining Cryo-EM structure of 4R tau](https://dss.niagads.org/datasets/ng00098/)
- [NG00099 – Results of gene-based weighted burden analyses using SCOREASSOC and GENEVARASSOC and multivariate analyses of variants near APOE applied to the ADSP Discovery Case-Control Based Extension Study.](https://dss.niagads.org/datasets/ng00099/)
- [NG00109 – Genetic architecture of subcortical brain structures in 38,851 individuals summary statistics](https://dss.niagads.org/datasets/ng00109/)
- [NG00110 – Exome-wide age-of-onset analysis reveals exonic variants in ERN1 and SPPL2C associated with Alzheimer’s disease](https://dss.niagads.org/datasets/ng00110/)
- [NG00111 – Genome-wide association identifies the first risk loci for psychosis in Alzheimer disease](https://dss.niagads.org/datasets/ng00111/)
- [NG00112 – A novel age-informed approach for genetic association analysis in Alzheimer’s disease summary statistics](https://dss.niagads.org/datasets/ng00112/)
- [NG00115 – Similar Genetic Architecture of Alzheimer’s Disease and Differential APOE Effect Between Sexes – Wang et al. 2021](https://dss.niagads.org/datasets/ng00115/)