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Table 2 Statistical test results in comparing our image-based method with voxel-based method

From: Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns

Folds Sections A vs. Neg. N vs. Neg. O vs. Neg. O vs. A A vs. N N vs. O
1.5 Coronal 0.0822 1.7E-06 4.7E-06 0.0036 1.7E-06 1.7E-06
  Sagittal 1.7E-06 8.5E-06 0.1306 2.9E-6 1.7E-06 2.1E-06
  Cor.+Sag. 3.5E-06 1.2E-05 0.0017 1.7E-06 2.6E-06 1.7E-06
10 Coronal 6.6E-04 1.7E-06 0.9263 9.3E-06 8.7E-05 0.7343
  Sagittal 0.0558 1.7E-06 5.5E-4 0.0916 0.0180 0.0052
  Cor.+Sag. 0.0387 1.1E-05 0.5038 0.1086 0.3389 0.4908
20 Coronal 0.0612 1.9E-06 0.9590 0.0001 0.7188 0.0100
  Sagittal 0.0387 0.0026 0.0157 2.7E-5 5.7E-6 0.0614
  Cor.+Sag. 0.6435 9.7E-05 0.0114 4.0E-4 0.3359 0.0349
  1. We employed two-sided Wilcoxon signed rank tests on the AUC values produced by 30 random trials, and the p-values were reported. We also performed the one-sided statistical test to compare the mean of image-based multiple trials with that of voxel-based method. The bold values indicate tasks on which image-based method outperforms voxel-based method significantly.