Skip to main content

Table 5 Results of applying the binary logistic regression model to the 7 datasets

From: How to get the most from microarray data: advice from reverse genomics

Cancer

Dataset

  

Variables in the model

–LOG(P)

m(AN)

M(T)

FC

SD(AN)

SD(T)

Breast

GDS3716

ns

Ns

Ns

ns

Ns

10.5(0.001)

Breast

GSE10780

ns

Ns

Ns

ns

Ns

76.1(<10-6)

Colorectal

GSE31737

5.2(0.02)

Ns

19.6(<10-6)1.5 E-82

ns

Ns

27.8(<10-6)

Lung

GSE18842

ns

Ns

13.1(<10-6)3.3 E-39

15.2(3.5 E-52)

6.5(0.01)

41.5(<10-6)

Lung

GSE19188

ns

Ns

Ns

ns

Ns

220.1(<10-6)

Prostate

GSE6919

7.9(0.005)

 

7.1(0.007)

ns

Ns

74.9(<10-6)

Prostate

GSE21034

22.3(<10-6)

 

4.8(0.04)

18.9

8.1(0.004)

48.8(<10-6)

  1. ns – the variable is not significant; numbers are Wald statistics for the variables in the model; significance is shown in parentheses.
Back to article page

BMC Genomics

ISSN: 1471-2164

Contact us