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:

  • about the process SeattleSNPs uses to generate high-quality genotyping data
  • how to find genes of interest to your research
  • to examine the detailed data available from SeattleSNPs
  • about educational opportunities provided by the SeattleSNPs team
TUTORIAL RELATED CONTENT

TUTORIALS

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

CATEGORIES

Variation & Medical : Resources that include information about sequence variation, phenotypes, or medically-relevant conditions.

BLOG POSTS

Tip of the Week: PolyPhen: There are several methods that can be used to predict if a particular non-synonymous SNP is deleterious; SIFT and PolyPhen, among others. Which one to use will be up to the individual researcher and th...

Tip of the Week: A year's worth of tips: So, this week we will have finished a full year of our "Tips of the Week" series. Every Wednesday we post a short 3-5 minute movie of a tip on how to use a resource or database. We've done one year's w...

SNPedia on the HapMap GBrowser: SNPs are hot. Everywhere we go for training people want to see SNPs. SNPs from many sources. And we know a lot of places to find them. Although everything gets in to dbSNP, of course, sometimes it help...

BIOMED CENTRAL

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