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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.