Genomics and genome-wide association studies: an integrative approach to expression QTL mapping - PubMed (original) (raw)

Genomics and genome-wide association studies: an integrative approach to expression QTL mapping

James H Degnan et al. Genomics. 2008 Sep.

Abstract

Expression QTL mapping by integrating genome-wide gene expression and genotype data is a promising approach to identifying functional genetic variation, but is hampered by the large number of multiple comparisons inherent in such studies. A novel approach to addressing multiple testing problems in genome-wide family-based association studies is screening candidate markers using heritability or conditional power. We apply these methods in settings in which microarray gene expression data are used as phenotypes, screening for SNPs near the expressed genes. We perform association analyses for phenotypes using a univariate approach. We also perform simulations on trios with large numbers of causal SNPs to determine the optimal number of markers to use in a screen. We demonstrate that our family-based screening approach performs well in the analysis of integrative genomic datasets and that screening using either heritability or conditional power produces similar, though not identical, results.

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Figures

Figure 1

Figure 1

Average number (out of 100) of causal SNPs detected as a function of the log10 number of the top k marker in the PBAT screen, k = 1, …, 10, 000, based on 1000 simulations and using either heritability or power as the screening criterion.

Figure 2

Figure 2

Heritability (top) and conditional power (bottom) plotted against p-values for one of the 1000 simulated data sets using noncausal SNPs only.

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