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The only considerable difference is that eQTL studies can involve a million or more expression microtraits. Standard gene mapping software packages can be used, although it is often faster to use custom code such as QTL Reaper or the web-based eQTL mapping system GeneNetwork.
Relationship between the minor allele frequency and the effect size of genome wide significant variants in a GWAS of height. Attempts have been made at creating comprehensive catalogues of SNPs that have been identified from GWA studies. [33] As of 2009, SNPs associated with diseases are numbered in the thousands. [34]
QTL location is indicated only by looking at which markers give the greatest differences between genotype group averages, and the apparent QTL effect at a marker will be smaller than the true QTL effect as a result of recombination between the marker and the QTL. Second, we must discard individuals whose genotypes are missing at the marker.
Association mapping has been most widely applied to the study of human disease, specifically in the form of a genome-wide association study (GWAS). A genome-wide association study is performed by scanning an entire genome for SNPs associated with a particular trait of interest, or in the case of human disease, with a particular disease of interest.
The aim of PheWAS studies (or PheWASs) is to examine the causal linkage between known sequence differences and any type of trait, including molecular, biochemical, cellular, and especially clinical diagnoses and outcomes. [2] [3] [4] It is a complementary approach to the genome-wide association study, or GWAS, methodology. [5]
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.