Learn to use SeattleSNPs with this free tutorial, sponsored by SeattleSNPs. SeattleSNPs identifies, genotypes, and models the associations between single nucleotide polymorphisms (SNPs) in candidate genes and pathways that underlie inflammatory responses in humans. Users can visualize these high-density SNPs and access the underlying data in many forms--both text and graphical representations. This is an invaluable tool for any researcher working with single nucleotide polymorphisms (SNPs).
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
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.
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Recent BioMed Central research articles citing this resource
Resler J Alexa et al., Genetic variation in TLR or NFkappaB pathways and the risk of breast cancer: a case-control study Genetics, genomics and epigenetics. BMC Cancer (2013) doi:10.1186/1471-2407-13-219
Nolan K Daniel et al., Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5. BMC Genetics (2012) doi:10.1186/1471-2156-13-12
Yao Song et al., Variants in the vitamin D pathway, serum levels of vitamin D, and estrogen receptor negative breast cancer among African-American women: a case-control study. Breast Cancer Research (2012) doi:10.1186/bcr3162
Webb A Elizabeth et al., Difficulties in finding DNA mutations and associated phenotypic data in web resources using simple, uncomplicated search terms, and a suggested solution. Human Genomics (2011) doi:10.1186/1479-7364-5-3-141
Cagliani Rachele et al., Balancing selection is common in the extended MHC region but most alleles with opposite risk profile for autoimmune diseases are neutrally evolving. BMC Evolutionary Biology (2011) doi:10.1186/1471-2148-11-171