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Table 3 Comparison of single gene classifiers and standard classifiers

From: Microarray-based cancer prediction using single genes

Parameter
Dataset
Smallest
p-valuea
t-test statisticb Fold changec # Significant gened Accuracy (%) of standard classifierse Accuracy (%) of single gene classifiersf
Melanoma 1.37e-29 22.68 277.78 7263 97 96.5
Breast Cancer 1 8.10e-06 9.06 3.65 20 52.2 66
Brain Cancer 1.51e-04 4.06 21.73 15 67 78.5
Breast Cancer 2 3.10e-06 5.16 3.48 180 70 54
Gastric Tumor 7.34e-10 9.51 10 4798 92.2 84.5
Lung Cancer 1 2.51e-21 20.34 1923.48 7561 97.2 96.5
Lung Cancer 2 6.82e-35 24.72 505.16 3219 99 93
Lymphoma 1.50e-04 4.07 1.33 2 58.5 72.5
Myeloma 5.00e-07 5.23 4.49 172 76.5 67.5
Pancreatic Cancer 1.30e-06 5.37 5.88 58 61 79.5
Prostate Cancer 1.34e-21 12.53 12.82 812 89.3 89
  1. Note:
  2. aThe minimum univariate t-test p-value for the genes significantly different between the classes.
  3. bThe absolute value of the t-test statistic corresponding to the left smallest p-value.
  4. cThe maximum fold change in the geometry mean of gene expression between the classes,
  5. dThe total number of genes significantly different between the classes at 0.001 significance level.
  6. eThe mean classification accuracy of the four standard classifiers.
  7. fThe mean classification accuracy of the two single gene classifiers.