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
t-test
SAM
t-test
SAM
t-test
SAM
t-test
SAM

A
MAS 4
MAS 4
t-test
[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
t-test


[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
t-test




[180]
95 (50 %)
109 (35%)
76 (32%)
F
Rank remap
dChip
SAM





[105]
68 (24%)
67 (59%)
G
NP
dChip
t-test






[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 array-to-array 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 MAS 4, Affymetrix analysis software version 4.0; dChip, dChip software [8]; Rank remap, unpublished method of D.A.H; NP, nonparametric method of Sidirov et al.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]; t-test, Student T statistic; SAM, statistical analysis of microarrays software [10].

Hosack et al. Genome Biology 2003 4:R70   doi:10.1186/gb-2003-4-10-r70

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