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To overcome the difficulty of identifying common variants that are associated with YOH, we performed several multilocus association tests and interaction tests and successfully identified some novel YOH disease genes.
Fourth, we performed genome-wide multilocus association tests using either the haplotype association test or p-value combination test.
Next, we verified the significant findings obtained from genome-wide multilocus association tests and the interaction tests.
By using different methodological constructions, the multilocus association tests and interaction analyses were able to detect genes involved in joint and interactive models, respectively.
Single-locus association tests, multilocus association tests and pair-wise gene-gene interaction tests were performed to identify young-onset hypertension susceptibility genes.
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Using 91,713 SNPs with good quality (see the discussion of statistical methods), we investigated marginal effects (genome-wide single-locus association test), joint effects (genome-wide multilocus association test) and interactive effects (genome-wide pair-wise interaction test) of SNPs on YOH.
To increase the test power, in addition to the single-locus association test, we used various multilocus association methods, including the p-value combination approach [29], haplotype analysis [27], [34] and interaction analysis [23] [26], [30], to compensate for the limitations of the single-locus association test and to examine fully the genetic complexity of hypertension.
RESULTS: An association analysis using both allelic and genotypic single-locus tests revealed a significant association between the risk for spina bifida and 3 polymorphisms in the gene ALDH1A2; however, we found no evidence of a significant multilocus association.
performing association tests on imputed genotypes.
As described previously [8], the PDT statistic [33] functions within the framework of the MDR algorithm to evaluate multilocus association in pedigrees.
The fully conditional posterior densities for the multilocus association model (1) parameters are as follows.
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