Data sharing
Genomic data sharing plays a crucial role in advancing scientific research and medical discoveries and involves the voluntary contribution of genetic data by individuals, researchers, and institutions to publicly accessible databases.
Genomic datasets and data sharing
Genomic data sharing plays a crucial role in advancing scientific research and medical discoveries and involves the voluntary contribution of genetic data by individuals, researchers, and institutions to publicly accessible databases.
This collective sharing of this data fosters collaboration, accelerates scientific progress, and enables researchers worldwide. By pooling together diverse genomic datasets, scientists can identify patterns, uncover genetic associations with diseases, develop targeted therapies, and ultimately improve healthcare outcomes for individuals and populations.
NIAGADS is a repository that facilitates the deposition and sharing of genomic data from the ADSP and other NIA funded Alzheimer’s Disease and Related Dementias genomic studies with approved users in the research community.
NIAGADS Data
The NIAGADS Data Sharing Service (DSS) is a repository that facilitates the deposition and sharing of genomic data from the ADSP and other NIA funded Alzheimer’s Disease and Related Dementias genomic studies with approved users in the research community.
Take a look at the datasets available in NIAGADS.
Learn what documents and procedures are required to submit data to NIAGADS.
Alzheimer’s Disease Sequencing Project (ADSP)
The Alzheimer’s Disease Sequence Project (ADSP) group is analyzing whole genome and whole exome sequence data generated from samples relevant to Alzheimer’s disease. The ADSP invites collaborations with other investigators.
The Memory and Aging Project (MAP) at the Knight-ADRC (Washington University in St. Louis) collects cognitive data, biological samples and imaging from studies of participants over many years (longitudinal research). This clinical information combined with extensive testing and analyzing will lead to the identification of novel genetic modifiers, protective variants, molecular biomarkers and the novel targets.