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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. GeneNetwork hosts many large eQTL mapping data sets and provide access to fast algorithms to map single loci and epistatic interactions. As is true in all QTL mapping studies ...
A quantitative trait locus (QTL) is a locus (section of DNA) that correlates with variation of a quantitative trait in the phenotype of a population of organisms. [1] QTLs are mapped by identifying which molecular markers (such as SNPs or AFLPs) correlate with an observed trait.
In statistical genetics, inclusive composite interval mapping (ICIM) has been proposed as an approach to QTL (quantitative trait locus) mapping for populations derived from bi-parental crosses. QTL mapping is based on genetic linkage map and phenotypic data to attempt to locate individual genetic factors on chromosomes and to estimate their ...
Fine-mapping is a process to refine these lists of associated variants to a credible set most likely to include the causal variant. Fine-mapping requires all variants in the associated region to have been genotyped or imputed (dense coverage), very stringent quality control resulting in high-quality genotypes, and large sample sizes sufficient ...
In genetics, association mapping, also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of historic linkage disequilibrium to link phenotypes (observable characteristics) to genotypes (the genetic constitution of organisms), uncovering genetic associations.
Statistical frameworks and mapping models are used to identify imprinting effects on genes and complex traits. Allelic parent-of-origin influences the vary in phenotype that derive from the imprinting of genotype classes. [65] These models of mapping and identifying imprinting effects include using unordered genotypes to build mapping models. [67]
An alternative approach is to use paired-end reads, when a potentially large number of paired reads would map each end to a different exon, giving better coverage of these events (see figure). Nonetheless, the end result consists of multiple and potentially novel combinations of genes providing an ideal starting point for further validation.
Retrieved from "https://en.wikipedia.org/w/index.php?title=EQTL&oldid=325601226"This page was last edited on 13 November 2009, at 10:52 (UTC). (UTC).