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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 candidate gene approach to conducting genetic association studies focuses on associations between genetic variation within pre-specified genes of interest, and phenotypes or disease states. This is in contrast to genome-wide association studies (GWAS), which is a hypothesis-free approach that scans the entire genome for associations between ...
Consequently, transcript abundance might be considered as a quantitative trait that can be mapped with considerable power. These have been named expression QTLs (eQTLs). [ 12 ] The combination of whole-genome genetic association studies and the measurement of global gene expression allows the systematic identification of eQTLs.
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.
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]
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