摘要
AIM： To propose a new meta-analysis method for bi-variate P value which account for the paired structure. METHODS： Studies that look to test two different fea-tures from the same sample gives rise to bivariate Pvalue. A relevant example of this is testing for periodici-ty as well expression from time-course gene expressionstudies. Kocak et al （2010） uses George and Mudholkar’（1983） “Difference of Two Logit-Sums” method to poolbivariate P value across independent experiments, as-suming independence within a pair. As bivariate P valueneed not to be independent within a given study, wepropose a new meta-analysis approach for pooling bi-variate P value across independent experiments, whichaccounts for potential correlation between paired P-val-ues. We compare the “Difference of Two Logit Sums”method with our novel approach in terms of their sen-sitivity and specifcity through extensive simulations by generating P value samples from most commonly used tests namely, Z test, t test, chi-square test, and F test, with varying sample sizes and correlation structure. RESULTS： The simulations results showed that our new meta-analysis approach for correlated and uncor-related bivariate P value has much more desirable sen-sitivity and specifcity features compared to the existing method, which treats each member of the paired P value as independent. We also compare these meta-analysis approaches on bivariate P value from periodici-ty and expression tests of 4936 S.Pombe genes from 10 independent time-course experiments and we showed that our new approach ranks the periodic, conserved, and cycling genes significantly higher, and detects many more periodic, “conserved” and “cycling” genes among the top 100 genes, compared to the ‘Difference of Two Logit-Sums’ method. Finally, we used our meta-analytic approach to compare the relative evidence in the association of pre-term birth with preschool wheez-ing versus pre-school asthma.CONCLUSION： The new meta-analysis method has much better sensitivity and specifc characteristics com-pared to the “Difference of Two-Logit Sums” method and it is not computationally more expensive.
AIM: To propose a new meta-analysis method for bivariate P value which account for the paired structure.METHODS: Studies that look to test two different features from the same sample gives rise to bivariate P value.A relevant example of this is testing for periodicity as well expression from time-course gene expression studies.Kocak et al(2010) uses George and Mudholkar'(1983) "Difference of Two Logit-Sums" method to pool bivariate P value across independent experiments,assuming independence within a pair.As bivariate P value need not to be independent within a given study,we propose a new meta-analysis approach for pooling bivariate P value across independent experiments,which accounts for potential correlation between paired P-values.We compare the "Difference of Two Logit Sums"method with our novel approach in terms of their sensitivity and specificity through extensive simulations by generating P value samples from most commonly used tests namely,Z test,t test,chi-square test,and F test,with varying sample sizes and correlation structure.RESULTS: The simulations results showed that our new meta-analysis approach for correlated and uncorrelated bivariate P value has much more desirable sensitivity and specificity features compared to the existing method,which treats each member of the paired P value as independent.We also compare these meta-analysis approaches on bivariate P value from periodicity and expression tests of 4936 S.Pombe genes from 10 independent time-course experiments and we showed that our new approach ranks the periodic,conserved,and cycling genes significantly higher,and detects many more periodic,"conserved" and "cycling" genes among the top 100 genes,compared to the ‘Difference of Two Logit-Sums' method.Finally,we used our metaanalytic approach to compare the relative evidence in the association of pre-term birth with preschool wheezing versus pre-school asthma.CONCLUSION: The new meta-analysis method has much better sensitivity and specific characteristics compared to the "Difference of Two-Logit Sums" method and it is not computationally more expensive.
