Skip to main content

Table 6 Results for models trained and tested with mouse data

From: A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts

Test data set

 

Method

GRCm38 (mm10)

Radial using GRCm38 and first ORF

  Sensitivity

9 8 . 7 0 %

  Specificity

96.96%

  Accuracy

9 7 . 8 3 %

CPCa

  Sensitivity

75.46%

  Specificity

9 8 . 3 7 %

  Accuracy

86.91%

CPATa

  Sensitivity

95.34%

  Specificity

88.17%

  Accuracy

91.76%

lncRScan-SVMa

Sensitivity

95.29%

  Specificity

89.14%

  Accuracy

92.21%

iSeeRNAb,c

  Sensitivity

94.20%

  Specificity

92.70%

  Accuracy

93.45%

FEELncd

  Sensitivity

94.10%

  Specificity

93.80%

  Accuracy

93.90%

  1. Results in bold are the best ones for each test data set
  2. aResults obtained in Han et al. [25]
  3. bResults obtained in Sun et al. [27]
  4. cThis method was created to classify only lincRNAs
  5. dResults obtained in Wucher et al. [28]