Table 3 

EASE themes are consistent despite the poor overlap of gene lists derived from the same experiment by various analytical methods 

Method 
A 
B 
C 
D 
E 
F 
G 
H 

Normalization 
MAS 4 
MAS 4 
dChip 
dChip 
Rank remap 
Rank remap 
NP 
NP 

Intensity calculation 
MAS 4 
MAS 4 
dChip 
dChip 
dChip 
dChip 
dChip 
dChip 

Method 
Normalization 
Intensity calculation 
Gene selection 
ttest 
SAM 
ttest 
SAM 
ttest 
SAM 
ttest 
SAM 


A 
MAS 4 
MAS 4 
ttest 
[72] 
72 (60%) 
20 (7%) 
17 (12%) 
18 (8%) 
19 (12%) 
24 (8%) 
22 (10%) 
B 
MAS 4 
MAS 4 
SAM 
[120] 
27 (9%) 
22 (12%) 
25 (9%) 
25 (13%) 
34 (10%) 
31 (12%) 

C 
dChip 
dChip 
ttest 
[220] 
81 (36%) 
130 (48%) 
70 (27%) 
105 (29%) 
71 (22%) 

D 
dChip 
dChip 
SAM 
[86] 
56 (27%) 
55 (40%) 
49 (18%) 
47 (27%) 

E 
Rank remap 
dChip 
ttest 
[180] 
95 (50 %) 
109 (35%) 
76 (32%) 

F 
Rank remap 
dChip 
SAM 
[105] 
68 (24%) 
67 (59%) 

G 
NP 
dChip 
ttest 
[242] 
154 (59%) 

H 
NP 
dChip 
SAM 
[173] 



Gene lists resulting from the same experiment can differ greatly as a result of selection criteria. Eight different methods were used to select genes upregulated in peripheral blood mononuclear cells (PBMCs) of HIV patients after discontinuation of antiretroviral drug therapy. The various lists resulted from four different arraytoarray normalizations, two different methods of intensity calculation and two methods of statistical selection of genes (see text). The values in square brackets on the diagonal show the total number of genes yielded by each method. The unbracketed numbers give the absolute number of genes shared by any two methods, with the percentage of genes in both lists from the combined gene lists in parentheses. MAS 4, Affymetrix analysis software version 4.0; dChip, dChip software [8]; Rank remap, unpublished method of D.A.H; NP, nonparametric method of Sidirov et al. [9]; ttest, Student T statistic; SAM, statistical analysis of microarrays software [10]. 

Hosack et al. Genome Biology 2003 4:R70 doi:10.1186/gb2003410r70 