A Novel Statistic for Genome-Wide Interaction Analysis
Xuesen Wu,
Hua Dong,
Li Luo,
Yun Zhu,
Gang Peng,
John D Reveille and
Momiao Xiong
PLOS Genetics, 2010, vol. 6, issue 9, 1-15
Abstract:
Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pgen00:1001131
DOI: 10.1371/journal.pgen.1001131
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