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Hence, GWAS is a non-candidate-driven approach, in contrast to gene-specific candidate-driven studies. GWA studies identify SNPs and other variants in DNA associated with a disease, but they cannot on their own specify which genes are causal. [1] [2] [3] The first successful GWAS published in 2002 studied myocardial infarction. [4]
Over the years, the GWAS catalog has enhanced its data release frequency by adding features such as graphical user interface, ontology-supported search functionality and a curation interface. [3] The GWAS catalog is widely used to identify causal variants and understand disease mechanisms by biologists, bioinformaticians and other researchers.
GWAS Central is a core component of the GEN2PHEN project and intends to provide an operational model, plus an open-source software package, so others can create similar databases across the world. These will be hosted by institutes, consortia, and even individual laboratories; providing those groups a toolkit for publicising and publishing ...
A genome-wide association study, or GWAS, is a genetic tool that uses single nucleotide polymorphisms, or SNPs, to identify if a trait or disease is linked to a specific genetic variant. By observing if frequencies of a specific variant are more commonly associated, or higher than expected, with the given trait; an association is developed ...
In the field of genetic sequencing, genotyping by sequencing, also called GBS, is a method to discover single nucleotide polymorphisms (SNP) in order to perform genotyping studies, such as genome-wide association studies (). [1]
In genome-wide association studies, genome-wide significance (abbreviated GWS) is a specific threshold for determining the statistical significance of a reported association between a given single-nucleotide polymorphism (SNP) and a given trait.
The first genome-wide association study (GWAS) of ALS was published in 2007, and 14 GWASs total had been published through 2013. They have contributed significantly to our understanding of ALS genetics; for example, a 2010 GWAS studying ALS in Finland led to discovery of the role of mutations at the C9orf72 locus in ALS. However, a gene ...
[2] [3] [4] It is a complementary approach to the genome-wide association study, or GWAS, methodology. [5] A fundamental difference between GWAS and PheWAS designs is the direction of inference: in a PheWAS it is from exposure (the DNA variant) to many possible outcomes, that is, from SNPs to differences in phenotypes and disease risk.