Learn to use dbGaP, the NCBI database of Genotypes and Phenotypes that serves as a repository for the results of studies investigating the interaction between genotypes and phenotypes. The dbGaP resource includes detailed reports of variables, documents, analyses, and data sets from genome wide association studies and other large-scale studies that use high throughput genotyping and sequencing methods. Learn about the two levels of access to dbGaP, open and controlled, and how to search and retrieve open access data. The dbGaP resource compiles studies using stable identifiers and standard formats that allow these data to be browsed, downloaded, and used to facilitate additional studies and replication of results.
You will learn:
This tutorial is a part of the tutorial group Human variations. You might find the other tutorials in the group interesting:
GAD: Genetic Association Database: An archived database associating human genes and polymorphisms with diseases
Madeline 2.0: Human pedigree diagram tools
DrugBank: A chemoinformatics and bioinformatics resource
DGV: Database of Genomic Variants: Database of Genomic Variants, DGV, catalogs and displays structural variation in the human genome
OMIM: Online Mendelian Inheritance in Man (OMIM): A database of human genes, genetic diseases and disorders
CGAP: Characterize the molecular genetic changes that cause a normal cell to become a cancer cell
ENCODE Foundations: ENCyclopedia of DNA Elements
GeneSNPs: An integrated view of gene structure and SNP variations
NIEHS SNPs: National Institute for Environmental Health Sciences Environmental Genome Project (EGP) SNPs
HapMap: HapMap, a database and analysis resource of human variation
Genetics Home Reference: A collection of data describing the effects of genetic variability on human health and disease
SeattleSNPs: Human SNPs in genes
dbSNP: NCBI's SNP database
GeneTests: GeneTests, a current, comprehensive genetic testing resource
Variation & Medical : Resources that include information about sequence variation, phenotypes, or medically-relevant conditions.
NCBI : This category includes resources maintained at the National Center for Biotechnology Information (NCBI).
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Recent BioMed Central research articles citing this resource
Rahmani Elior et al., Genome-wide methylation data mirror ancestry information. Epigenetics Chromatin (2017) doi:10.1186/s13072-016-0108-y
Joehanes Roby et al., Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies. Genome Biology (2017) doi:10.1186/s13059-016-1142-6
Hakenberg Jörg et al., Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts Sequence analysis (applications). BMC Bioinformatics (2016) doi:10.1186/s12859-015-0865-9
Zhang Wangshu et al., Inference of domain-disease associations from domain-protein, protein-disease and disease-disease relationships. BMC Systems Biology (2016) doi:10.1186/s12918-015-0247-y
Yang J. James et al., An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function Comparative genomics. BMC Bioinformatics (2016) doi:10.1186/s12859-015-0868-6