Learn to use The Database of Genomic Variants, or DGV , a curated catalog of structural variation within the human genome. All variation data is from normal non-diseased controls, yet the ramifications of the data go well beyond their role in normal phenotypic variability. Many highly variable regions are extremely important in disease and this field is only in its infancy currently. Copy-number variations, or CNVs, are under active pursuit. DGVs user-friendly format allows you to easily browse variation data in tabular or graphic format organized by chromosome location. Users can search by keywords, chromosome location, genes, sequence and more. Each variation entry has extensive details including where the original data was extracted from, links to many other resources, methodology, study details and the ability to view and manipulate your data using the DGVs GBrowse-based genome browser or UCSC and Ensembl's genome browsers.
Note: A new version of DGV has just launched. We will update this material soon to correspond with the new interface. Many of the concepts will remain the same, and a track of the data from the prior version will be available. For more details, see: Official Launch of the new Database of Genomic Variants (DGV) .
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
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
dbGaP: A database of genotypes and phenotypes with extensive variation data and clinical details
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.
Official Launch of the new Database of Genomic Variants (DGV): The Database of Genomic Variants (DGV) has been working on a new site for a while. It's been available as a beta site to get used to it and kick the tires, but now it's ready for prime time. They are r...
Video Tip of the Week: The New Database of Genomic Variants - DGV2 (edited): In today's tip I will briefly introduce you to the beta version of the updated DGV resource. The Database of Genomic Variants, or DGV, was created in 2004 at a time early in the understanding of human...
Tip of the Week: MutaDATABASE, a centralized and standardized DNA variation database: We all know and love dbSNP, and DGV, and 1000 Genomes, and HapMap, and OMIM, and the couple of other dozen variation databases I can think of off the top of my head. But--even though there's a lot of ...
Changes to DGV display standards (and yay standards!): This notice came from DGV (Database of Genomic Variants) while I was on vacation last week, but I wanted to highlight this for a couple of reasons. First--it's very cool that these groups have now chos...
Friday SNPpets: Welcome to our Friday feature link collection: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don't make it to a blog post. Here they are for your e...
Recent BioMed Central research articles citing this resource
Mehrban Hossein et al., Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture. Genetics Selection Evolution (2017) doi:10.1186/s12711-016-0283-0
Hernandez-Ferrer Carles et al., MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration Results and data. BMC Bioinformatics (2017) doi:10.1186/s12859-016-1455-1
Tebel Katrin et al., GenomeCAT: a versatile tool for the analysis and integrative visualization of DNA copy number variants Comparative genomics. BMC Bioinformatics (2017) doi:10.1186/s12859-016-1430-x
Ni Guiyan et al., Whole-genome sequence-based genomic prediction in laying chickens with different genomic relationship matrices to account for genetic architecture. Genetics Selection Evolution (2017) doi:10.1186/s12711-016-0277-y
Piccoli L. Mario et al., Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes Animal population genetics. BMC Genetics (2017) doi:10.1186/s12863-017-0475-9