title: Detection of cis-acting regulatory SNPs using allelic expression data.
abstract: Allelic expression (AE) imbalance between the two alleles of a gene can be used to detect cis-acting regulatory SNPs (rSNPs) in individuals heterozygous for a transcribed SNP (tSNP). In this paper, we propose three tests for AE analysis focusing on phase-unknown data and any degree of linkage disequilibrium (LD) between the rSNP and tSNP: a test based on the minimum P-value of a one-sided F test and a two-sided t test (proposed previously for phase-unknown data), a test the combines the F and t tests, and a mixture-model-based test. We compare these three tests to the F and t tests and an existing regression-based test for phase-known data. We show that the ranking of the tests based on power depends most strongly on the magnitude of the LD between the rSNP and tSNP. For phase-unknown data, we find that under a range of scenarios, our proposed tests have higher power than the F and t tests when LD between the rSNP and tSNP is moderate (∼0.2<<∼0.8). We further demonstrate that the presence of a second ungenotyped rSNP almost never invalidates the proposed tests nor substantially changes their power rankings. For detection of cis-acting regulatory SNPs using phase-unknown AE data, we recommend the F test when the rSNP and tSNP are in or near linkage equilibrium (<0.2); the t test when the two SNPs are in strong LD (<0.7); and the mixture-model-based test for intermediate LD levels (0.2<<0.7).
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. rxiao@mail.med.upenn.edu
authors.forename: Rui
authors.initials: R
authors.lastname: Xiao
authors.forename: Laura J
authors.initials: LJ
authors.lastname: Scott
mesh_terms: D000483:Alleles; D022981:Allelic Imbalance; D003198:Computer Simulation; D003951:Diagnostic Errors; D044127:Epigenesis, Genetic; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D016013:Likelihood Functions; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D017720:Molecular Epidemiology / Q000379:methods; D020641:Polymorphism, Single Nucleotide; D012333:RNA, Messenger / Q000378:metabolism; D012044:Regression Analysis
chemical_list: D012333:RNA, Messenger