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Prioritization of SNPs for genome-wide association studies using an interaction model of genetic variation, gene expression, and trait variation

Authors
Paik, H; Kim, J; Lee, S; Heo, HS; Hur, CG; Lee, D
Citation
Molecules and cells, 33(4):351-361, 2012
Journal Title
Molecules and cells
ISSN
1016-84780219-1032
Abstract
The identification of true causal loci to unravel the statistical evidence of genotype-phenotype correlations and the biological relevance of selected single-nucleotide polymorphisms (SNPs) is a challenging issue in genome-wide association studies (GWAS). Here, we introduced a novel method for the prioritization of SNPs based on p-values from GWAS. The method uses functional evidence from populations, including phenotype-associated gene expressions. Based on the concept of genetic interactions, such as perturbation of gene expression by genetic variation, phenotype and gene expression related SNPs were prioritized by adjusting the p-values of SNPs. We applied our method to GWAS data related to drug-induced cytotoxicity. Then, we prioritized loci that potentially play a role in druginduced cytotoxicity. By generating an interaction model, our approach allowed us not only to identify causal loci, but also to find intermediate nodes that regulate the flow of information among causal loci, perturbed gene expression, and resulting phenotypic variation.
MeSH terms
AlgorithmsEpistasis, GeneticGene ExpressionGene Regulatory Networks*Genetic Association Studies*Genetic Variation*Genome-Wide Association StudyHumansModels, TheoreticalPolymorphism, Single Nucleotide/*genetics
DOI
10.1007/s10059-012-2264-7
PMID
22460606
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Medical Informatics
AJOU Authors
백, 효정
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