Table 2 

Average formulation versus 95% probability formulation under the independent model.^{a} 

Average formulation: Univariate method 
95% probability formulation: Binomial method 




π_{1} 
λ_{0} 
n^{b} 
λ 
ϕ_{λ0} 
n^{c} 
λ 
ϕ_{λ0} 


5% 
60% 
9 
0.70 
0.985 
9 
0.70 
0.985 
70% 
9 
0.70 
0.576 
10 
0.81 
0.997 

80% 
10 
0.81 
0.681 
11 
0.88 
0.993 

90% 
12 
0.92 
0.866 
13 
0.95 
0.992 

10% 
60% 
8 
0.70 
0.999 
8 
0.70 
0.999 
70% 
8 
0.71 
0.687 
9 
0.82 
1.000 

80% 
9 
0.82 
0.841 
10 
0.89 
1.000 

90% 
11 
0.93 
0.977 
11 
0.93 
0.977 

20% 
60% 
7 
0.72 
1.000 
7 
0.72 
1.000 
70% 
7 
0.74 
0.975 
7 
0.74 
0.975 

80% 
8 
0.85 
0.996 
8 
0.85 
0.996 

90% 
9 
0.91 
0.792 
10 
0.95 
1.000 



a. Estimated sample size n, average sensitivity λ and probability ϕ_{λ0 }for the specified sensitivity λ_{0 }= 60%, 70%, 80%, 90%, under the independent model. The parameters used in the calculation were: m = 2,000, π_{1 }= 5%, 10%, 20%, δ_{0 }= 2 and q* = 0.05. b. Sample size n is computed by the univariate method from Equation (1) to achieve sensitivity λ_{0 }on average. c. Sample size n is calculated using Tsai et al. [7] method to ensure the probability ϕ_{λ0 }of detecting at least λ_{0 }fraction of differentially expressed genes is at least 95%. 

Lin et al. BMC Bioinformatics 2010 11:48 doi:10.1186/147121051148 