期刊
BIOINFORMATICS
卷 28, 期 3, 页码 403-410出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btr663
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- University of Georgia Research Computing Center
Motivation: Recently, gene-coexpression relationships have been found to be often conditional and dynamic. Many studies have suggested that single nucleotide polymorphisms (SNPs) have impacts on gene expression variations in human populations. Results: The SNPxGE(2) database contains the computationally predicted human SNP-coexpression associations, i.e. the differential coexpression between two genes is associated with the genotypes of an SNP. These data were generated from a large-scale association study that was based on the HapMap phase I data, which covered 269 individuals from 4 human populations, 556 873 SNPs and 15 000 gene expression profiles. In order to reduce the computational cost, the SNP-coexpression associations were assessed using gap/substitution models, proven to have a comparable power to logistic regression models. The results, at a false discovery rate (FDR) cutoff of 0.1, consisted of 44 769 and 50 792 SNP-coexpression associations based on single and pooled populations, respectively, and can be queried in the SNPxGE(2) database via either gene symbol or reference SNP ID. For each reported association, a detailed information page is provided.
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