2013
DOI: 10.3389/fgene.2013.00103
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Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma

Abstract: Increasing evidence suggests that single nucleotide polymorphisms (SNPs) associated with complex traits are more likely to be expression quantitative trait loci (eQTLs). Incorporating eQTL information hence has potential to increase power of genome-wide association studies (GWAS). In this paper, we propose using eQTL weights as prior information in SNP based association tests to improve test power while maintaining control of the family-wise error rate (FWER) or the false discovery rate (FDR). We apply the pro… Show more

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Cited by 59 publications
(68 citation statements)
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“…Our simulation results confirmed that the proposed weighting procedure dramatically improved the statistical power of GWA studies while controlling FWER at the nominal level, when gene expression is in the middle of the etiological pathway. Under this mechanism, our methods demonstrated greater power gain compared to that of Li et al [14]. It also provides ways to draw valuable information from massive data to assist functional interpretations of GWA signals.…”
Section: Discussionmentioning
confidence: 83%
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“…Our simulation results confirmed that the proposed weighting procedure dramatically improved the statistical power of GWA studies while controlling FWER at the nominal level, when gene expression is in the middle of the etiological pathway. Under this mechanism, our methods demonstrated greater power gain compared to that of Li et al [14]. It also provides ways to draw valuable information from massive data to assist functional interpretations of GWA signals.…”
Section: Discussionmentioning
confidence: 83%
“…In Table 1, we recorded the fraction of times that a SNP was declared significant at α=10.0510 for the four approaches: the conventional GWA analysis, the weight adjusted approach with ( WMPT) and without ( W MP ) trimming and Li’s approach [14]. The overall FWERs from the 10,000 simulations were estimated by counting the percent of times when any significant results were reported.…”
Section: Simulationmentioning
confidence: 99%
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