Power and sample size estimation in microarray studies

BMC Bioinformatics

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 _{λ 0}	n ^c	λ	ϕ _{λ 0}
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_{λ 0}for the specified sensitivity λ₀ = 60%, 70%, 80%, 90%, under the independent model. The parameters used in the calculation were: m = 2,000, π₁ = 5%, 10%, 20%, δ₀ = 2 and q* = 0.05.
b. Sample size n is computed by the univariate method from Equation (1) to achieve sensitivity λ₀ on average.
c. Sample size n is calculated using Tsai et al. [7] method to ensure the probability ϕ_{λ 0}of detecting at least λ₀ fraction of differentially expressed genes is at least 95%.

ISSN: 1471-2105