Table 1

Q-values for True Positives

Original

1

2

3

4

5

6

7

8


546_at

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

0.01

36311_at

<0.01

0.02

0.02

0.03

<0.01

<0.01

0.02

0.04

0.01

36889_at

<0.01

<0.01

0.03

0.03

<0.01

0.02

0.06

0.04

0.02

1091_at

<0.01

0.02

0.02

0.03

<0.01

0.01

0.02

0.02

0.01

39058_at

<0.01

0.02

0.02

0.03

<0.01

0.01

0.02

0.04

0.02

1024_at

<0.01

0.05

0.05

0.04

<0.01

0.02

0.1

0.1

0.02

37777_at

0.02

0.07

0.17

0.09

<0.01

0.1

0.31

0.42

0.04

684_at

0.02

0.08

0.13

0.09

<0.01

0.1

0.11

0.13

0.06

33818_at

0.08

0.11

0.24

0.49

<0.01

0.85

0.84

0.85

0.75

407_at

0.39

0.58

0.64

0.67

0.14

0.85

0.84

0.64

0.76

36202)_at

0.52

0.58

0.64

0.67

<0.01

0.85

0.84

0.85

0.76

1597_at

0.75

0.58

0.64

0.67

0.73

0.85

0.84

0.85

0.76

38734_at

0.75

0.58

0.64

0.67

0.46

0.85

0.84

0.85

0.76

36085_at

0.75

0.58

0.64

0.67

0.46

0.85

0.84

0.85

0.76

40322_at

0.75

0.58

0.64

0.67

0.46

0.85

0.84

0.85

0.76

1708_at

0.75

0.58

0.64

0.67

0.61

0.85

0.84

0.85

0.76


The q-values for each of the 16 spiked in probesets using all 8 arrays (Column 1) and with each of the 8 arrays removed (Columns 2-9). A q-value < 0.01 denotes a probeset correctly identified as differentially expressed. Removing the poor quality array (4) decreases the q-values, while removing the other good quality arrays increases the q-values.

McCall et al. BMC Bioinformatics 2011 12:137   doi:10.1186/1471-2105-12-137

Open Data