Figure 1.

A schematic outline of the hierarchical model. (a) Two SNPs that are significantly associated with expression level at the adjacent gene (in our method, association is measured using Bayes factors). (b) SNP 1 is located in regulatory annotations I, II and III, while SNP 2 is located in regulatory annotation I only. The numbers at the ends of the annotation bars illustrate the fold enrichment of eQTNs in each annotation: these are the exponential of the λl parameters of the hierarchical model. In practice, enrichment levels are estimated using all the genes simultaneously via a hierarchical model. These are combined in a logistic model to estimate the prior probability that any given SNP is an eQTN. (c) The hierarchical model assigns a posterior probability that each SNP is an eQTN, combining information from (a, b). Thus, even though the level of association with gene expression is similar for SNPs 1 and 2, more of the posterior probability is assigned to SNP1.

Gaffney et al. Genome Biology 2012 13:R7   doi:10.1186/gb-2012-13-1-r7
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