We compared FamCC and the TDT for an association study of hypertension in the Framingham Heart Study data and found a number of interesting results.
The modified FamCC statistic, which does not require estimating the pairwise genotype-phenotype correlations between family members, has reasonable type I error rates for both the family sample and the unrelated subsample. Moreover, on checking the inflation factor with FamCC for each trait, no obvious inflation of type I error was observed. Using FamCC to identify genes associated with hypertension, we found that although there are several SNPs deviating from the expected null distribution (Figure ), four of these SNPs were in strong LD, suggesting duplication of signals.
Using the same family sample, FamCC and FBAT produced different levels of significance for the same SNP in association testing of the three traits-hypertension, SBP, and DBP. Such differences also arose when comparing FBAT and the generalized estimating equation approach in a study by Levy et al. [16
]. These inconsistent results reflect the different information used by these two approaches and the fact that, because of these different assumptions, it is the alternative hypotheses that are different. For FBAT, the alternative hypothesis is one of both linkage and association, while for FamCC it is association only. FBAT, controls for population stratification by comparing transmitted with non-transmitted alleles from heterozygous parents, ignoring the information in homozygous parents, while FamCC applies principal components obtained from marker genotype data to adjust for any stratification in testing the null hypothesis of association only. FamCC uses all the available phenotype and genotype data, therefore the effective sample size for the TDT method is much smaller than that for FamCC, which would be expected to result in higher power for FamCC, as shown by Zhu et al. [9
]. Moreover, none of the detected SNPs reached the 0.05 significance level after correcting for multiple tests (corresponding to the nominal p
-value 2.5 × 10-6
). Thus, the SNPs identified by both FamCC and FBAT may only reflect the randomness of the p
-values under the null hypothesis. Because the information used and the alternative hypotheses assumed by FamCC and FBAT are not the same, observing inconsistent p
-values from the two methods is not surprising.