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Table 2 Significant coefficients of linear model for prognostics based on individual gene

From: Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences

Coefficient Estimate Standard error t value Pr (> | t | )
(Intercept) 1995.2 251.9 7.736 1.57×10−8
Handling, separate −1305.8 313.1 −4.171 2.51×10−4
Platform, HGU133 Plus 2.0: Handling, separate 3079.2 236.7 13.010 1.24×10−13
Platform, HGU133 Plus 2.0: Algorithm, log2 MAS5 −1844.8 409.9 −4.500 1.02×10−4
Platform, HGU133 Plus 2.0: Algorithm, MAS5 −1822.2 409.9 −4.445 1.18×10−4
Handling, separate: Algorithm, log2 MAS5 −1124.2 409.9 −2.743 1.03×10−2
Handling, separate: Algorithm, MAS5 −1132.8 409.9 −1.461 9.83×10−3
Handling, separate: Algorithm, RMA −993.0 409.9 −2.422 2.18×10−2
  1. For the linear model, Y = W + X + i = 1 5 Z i + W : X + i = 1 5 W : Z i + X : Z i where Y is the number of genes, W is the platform, X is the data handling and Z1…Z5 are specify the 6 options for the pre-processing algorithm, the coefficients that have a p < 0.05 are shown.