Detection of cis-acting regulatory SNPs using allelic expression data

Authors

  • Rui Xiao,

    Corresponding author
    1. Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
    2. Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Michigan
    • Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6021
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  • Laura J. Scott

    1. Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Michigan
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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<equation image<∼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 (equation image<0.2); the t test when the two SNPs are in strong LD (equation image<0.7); and the mixture-model-based test for intermediate LD levels (0.2<equation image<0.7). Genet. Epidemiol. 2011. © 2011 Wiley-Liss, Inc. 35: 515-525, 2011

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