Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Consortium to conduct genome-wide association studies (GWAS) to identify genes associated with an increased risk of developing late-onset Alzheimer''''s disease (LOAD). The goal of the ADGC is to identify genetic variants associated with risk for AD. It plans to do this through the following collaborative goals: # Identify genes responsible for AD susceptibility # Identify AD sub-phenotype genes rate-of-progression plaque / tangle load / distribution biomarker variability # Generate a genetic data resource for the AD research community Data generated by ADGC is available at the following website: https://www.niagads.org/content/alzheimers-disease-genetics-consortium-adgc-collection
Proper citation: Alzheimers Disease Genetics Consortium (RRID:SCR_004004) Copy
http://www.wikigenes.org/e/art/e/258.html
Consortium to discover and map the genes that contribute to Alzheimer's disease and completely understand the role inheritance plays. To achieve this goal, they will work to identify all the genes that contribute to the risk of developing this disease. Investigators will have access to combined genetic data from a large number of Alzheimer's disease subjects and compare it to genetic data from an equally large number of elderly people who do not have Alzheimer's. In the initial phase of the work, more than 20,000 people with Alzheimer's and about 20,000 healthy elderly subjects will be compared. As the study progresses, 10,000 additional people with Alzheimer's and the same number of healthy elderly subjects will be added to the study. The subjects for these studies come from different Alzheimer research project locations across Europe, the UK, the US, and Canada. Data is available from their 2014 publication in Translational Psychiatry at http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3944635/ (http://www.ncbi.nlm.nih.gov/pubmed/24495969) Currently, there is no public access to the raw individual level genetic data because of privacy considerations. Researchers working with US cohorts deposit data in the database of genotypes and phenotypes (dbGaP), where it is available to all researchers who can show that they are able to guarantee the security of the data. After scanning the DNA of over 74,000 patients and controls from 15 countries, the IGAP consortium reported 11 new regions of the genome involved in late-onset Alzheimer's disease. IGAP published its results in Nature Genetics on October 27, http://www.ncbi.nlm.nih.gov/pubmed/24162737
Proper citation: International Genomics of Alzheimers Project (RRID:SCR_004029) Copy
http://geneticassociationdb.nih.gov/
The Genetic Association Database is an archive of human genetic association studies of complex diseases and disorders. The goal of this database is to allow the user to rapidly identify medically relevant polymorphism from the large volume of polymorphism and mutational data, in the context of standardized nomenclature. The data is from published scientific papers. Study data is recorded in the context of official human gene nomenclature with additional molecular reference numbers and links. It is gene centered. That is, each record is a record of a gene or marker. If a study investigated 6 genes for a particular disorder, there will be 6 records. Anyone may view this database and anyone may submit records. You do not have to be an author on the original study to submit a record. All submitted records will be reviewed before inclusion in the archive. Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors. From a comprehensive search of the MeSH annotation of MEDLINE articles, they identified 3,342 environmental etiological factors associated with 3,159 diseases. They also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the etiome, which they define as the comprehensive compendium of disease etiology.
Proper citation: Genetic Association Database (RRID:SCR_013264) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the NIF Resources search. From here you can search through a compilation of resources used by NIF and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that NIF has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on NIF then you can log in from here to get additional features in NIF such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into NIF you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within NIF that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.