Learn to use the dbSNP resource, a large and valuable NCBI database that serves both as a repository for genomic variation data (including single nucleotide polymorphisms, microsatellites and small insertion/deletion mutations) and as a computational analysis resource. Learning to mine the dbSNP data will provide the researcher with extensive data and information about variations, evolution, disease and more. Understanding the structure of rs identifiers and ss identifiers will provide important conceptual features of SNP stored records within dbSNP and at other sites that employ dbSNP data. Access points from the dbSNP and the EntrezSNP interface will be explored.
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
NIEHS SNPs: National Institute for Environmental Health Sciences Environmental Genome Project (EGP) SNPs
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
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
GeneSNPs: An integrated view of gene structure and SNP variations
dbGaP: A database of genotypes and phenotypes with extensive variation data and clinical details
SeattleSNPs: Human SNPs in genes
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).
Video Tip of the Week: PheGenI, Phenotype-Genotype Integrator: The hunt for variations in genes and genomes has been both fruitful and frustrating. We can see genome variations in a variety of ways, but we can't always connect them with a phenotype easily. And vic...
What's the answer? (duplicate dbSNP IDs): BioStar is a site for asking, answering and discussing bioinformatics questions. We are members of the community and find it very useful. Often questions and answers arise at BioStar that are germane t...
Video Tip of the Week: VnD Resource for Genetic Variation and Drug Information: In today's tip I am going to feature a resource that I found recently. I've been updating our dbSNP tutorial, which Mary & Trey will be presenting at workshops in Morocco, and also our free PDB tutori...
What's the answer? (known disease mutations): BioStar is a site for asking, answering and discussing bioinformatics questions. We are members of the community and find it very useful. Often questions and answers arise at BioStar that are germane t...
dbSNP: no longer single....?: I think this is very interesting--dbSNP has a new logo. dbSNP is no longer "single". Keeping dbSNP as a professional name, but also has a new name for social situations: "Short Genetic Variations". I ...
Recent BioMed Central research articles citing this resource
McCarthy Marie Anne et al., The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms. Breast Cancer Research (2015) doi:10.1186/s13058-014-0509-4
Pousada Guillermo et al., Molecular and clinical analysis of TRPC6 and AGTR1 genes in patients with pulmonary arterial hypertension. Orphanet Journal of Rare Diseases (2015) doi:10.1186/s13023-014-0216-3
Parks Matthew et al., Impacts of low coverage depths and post-mortem DNA damage on variant calling: a simulation study. BMC Genomics (2015) doi:10.1186/s12864-015-1219-8
Wu Xiaowei et al., Nonparametric Bayesian clustering to detect bipolar methylated genomic loci. BMC Bioinformatics (2015) doi:10.1186/s12859-014-0439-2
Mustaki U et al., A patient with Trisomy 13 mosaicism: review and case report International Conference for Healthcare and Medical Students (ICHAMS) 2013 International Conference for Healthcare and Medical Students (ICHAMS) 2013. BMC Proceedings (2015) doi:10.1186/1753-6561-9-S1-A51