Ranking analysis of F-statistics for microarray data

BMC Bioinformatics

Table 1 Efficiencies of different methods in identifying genes differentially expressed among four groups each with 6 replicates in 30 simulated datasets

		NGCS			ENFP			TNFP			Difference between ENFP and TNFP
Method	FDR	Mean (SD)	Min	Max	Mean (SD)	Min	Max	Mean (SD)	Min	Max	$\| \bar{d} \|$	Var (d)	C(d ≥ 0)
B procedure	λ = 0.05	59.6 (6.6)	46	73	3.0 (0.3)	2	4	0.0(0.0)	0	0	3.0		100%
BH Procedure	λ = 0.05	102.2 (9.9)	81	119	4.8 (1.0)	4	6	1.6 (1.4)	0	6	3.2		97%
SAM	0.04 <λ ≤ 0.05	111.5(14.3)	89	129	5.1 (0.6)	5	6	5.6(2.8)	2	12	2.0	6.7	56.5%
	0.03 <λ ≤ 0.04	106.8(13.2)	84	119	3.7 (0.6)	3	5	3.8(2.3)	0	8	1.5	4.0	66.7%
	0.02 <λ ≤ 0.03	96.2(12.5)	80	119	2.3 (0.6)	1	3	3.1(1.7)	1	6	1.4	3.1	39.4%
	0.01 <λ ≤ 0.02	91.0(12.7)	71	107	1.3 (0.47)	1	2	1.6(1.2)	0	4	0.9	1.1	67.5%
	0.00 <λ ≤ 0.01	98.7(6.6)	94	108	0.9 (0.1)	1	1	1.5(1.1)	0	3	1.0	1.9	36.4%
	λ = 0.00	82.9(11.0)	66	108	0.0 (0.0)	0	0	1.0(0.6)	0	3	1.0	1.4	23.1%
RAF	0.04 <λ ≤ 0.05	115.1 (9.2)	96	131	5.1 (0.4)	4	6	4.4(2.7)	1	9	2.2	7.3	75.0%
	0.03 <λ ≤ 0.04	110.6(12.2)	85	128	3.9 (0.6)	3	5	3.2(2.1)	1	8	1.6	3.9	79.2%
	0.02 <λ ≤ 0.03	103.6 (10.6)	86	120	2.7 (0.5)	2	3	2.1(1.5)	0	6	1.3	2.8	81.8%
	0.01 <λ ≤ 0.02	100.7 (10.8)	81	118	1.7 (0.5)	1	2	1.1(0.9)	0	3	0.9	1.3	75.8%
	0.00 <λ ≤ 0.01	100.8 (4.1)	96	112	1.1 (0.2)	1	2	0.7(1.0)	0	3	0.9	1.4	77.8%
	λ = 0.00	83.8 (7.1)	69	95	0.0 (0.0)	0	0	0.1(0.3)	0	1	0.1	0.1	86.2%

FDR, false discovery rate; NGCS, number of genes called significant; ENFP, estimated number of false positives; TNFP, true number of false positives.
$| \bar{d} | = \frac{1}{N_{λ}} \sum_{k = 1}^{N_{λ}} | d_{k} |$ where d_k= ENFP_K- TNFP_Kand N_λis number of x <λ ≤ y in 30 simulations. $C (d \geq 0) = \sum_{k = 1}^{N_{λ}} I_{k} / N_{λ}$ where I_k= 1 if d_k≥ 0, otherwise, I_k= 0. $V a r (d) = \frac{1}{N_{λ} - 1} \sum_{k = 1}^{N_{λ}} {(d_{k} - 0)}^{2} = \frac{1}{N_{λ} - 1} \sum_{k = 1}^{N_{λ}} d_{k}^{2}$ .

ISSN: 1471-2105