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Table 1 The accuracy, sensitivity, specificity, PPV, NPV and AUC of SVM analysis of brown and red modules

From: Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics

Modules Num of genes Correct rate Se Sp PPV NPV AUC
Brown
 1–5 genes 5 0.692 0.882 0.333 0.714 0.600 0.810
 1–10 genes 10 0.731 0.938 0.400 0.714 0.800 0.743
 1–15 genes 15 0.808 0.944 0.500 0.810 0.800 0.800
 1–20 genes 20 0.808 0.900 0.500 0.857 0.600 0.733
 1–25 genes 25 0.846 0.905 0.600 0.905 0.600 0.914
 1–30 genes 30 0.885 1.000 0.450 0.857 1.000 0.933
 1–35 genes 35 0.885 0.950 0.667 0.905 0.800 0.895
 1–40 genes 40 0.923 1.000 0.714 0.905 1.000 0.905
Red
 1–5 genes 5 0.654 0.833 0.750 0.714 0.400 0.686
 1–10 genes 10 0.808 0.900 0.500 0.857 0.600 0.743
 1–15 genes 15 0.885 0.875 1.000 1.000 0.400 0.943
 1–20 genes 20 0.885 0.910 0.750 0.952 0.600 0.857
 1–25 genes 25 0.885 0.950 0.667 0.905 0.800 0.800
  1. Se, sensitivity; Sp, specificity; PPV, positive prediction value; NPV, negative prediction value; AUC, area under ROC curve