Meta-analysis of bivariate P values

Table 1 The estimates of α0, α1, α2, α3 in the approximating cumulative distribution function function

Sample size	α0	α1	α2	α3
3	-0.7842	0.0822	4.5194	1.4353
4	-1.2092	0.071	6.9087	1.5018
5	-1.5419	0.0639	9.6286	1.5474
6	-1.8161	0.0596	12.6637	1.5761
7	-2.0475	0.0557	15.9471	1.6005
8	-2.2507	0.0528	19.555	1.6202
9	-2.4347	0.0511	23.4612	1.6324
10	-2.5823	0.0493	27.1803	1.6403

Table 2 Simulation design for Bivariate meta-analysis

Scenario	Distribution-1	Distribution-2	Comment
1	Beta(1,1)	Beta(1,1)	Null Case
2	Z test, Δ = 0.5	Z test, Δ = 0.25	One-sample Z test with sample size = 10
3	T test, Δ = 0.5	T test, Δ = 0.25	One-sample t test with sample size = 10
4	χ2 test, Δ = 1.5	χ2 test, Δ = 1.25	One-sample χ2 test of variance with sample size = 10
5	F test, Δ = 0.5	F test, Δ = 0.25	One-way ANOVA with three class-levels of size = 10

Table 3 Performance of the new meta-analysis method compared to the “Difference of Two Logit Sums” method on detecting periodic, conserved and cycling genes

Method	Periodic genes by Marguerat et al[10] (2006) n = 40		Conserved genes by Lu et al[11] (2007) n = 52		Cycling genes by Lu et al[11] (2007)n = 235
	Median rank	No. of genes in top 100 genes	Median rank	No. of genes in top 100 genes	Median rank	No. of genes in top 100 genes
Difference of two logit sums	4072	0	3738	2	3405	5
New meta-analysis method	102	20	697	13	745	37