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Table 2 Results of the human case study

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

Test data set

  

Model

GRCh37

GRCh38

Radial using GRCh37 and first ORF

  Sensitivity

98.95%

99.43%

  Specificity

97.41%

97.23%

  Accuracy

98.18%

98.33%

Radial using GRCh37 and longest ORF

  Sensitivity

98.09%

98.73%

  Specificity

97.50%

97.55%

  Accuracy

97.80%

98.14%

Quadratic using GRCh37 and first ORF

  Sensitivity

98.15%

98.83%

  Specificity

96.60%

96.41%

  Accuracy

97.38%

97.62%

Quadratic using GRCh37 and longest ORF

  Sensitivity

94.79%

95.54%

  Specificity

97.23%

97.19%

  Accuracy

96,01%

96.36%

Radial using GRCh38 and first ORF

  Sensitivity

89.86%

97.54%

  Specificity

98.64%

99.26%

  Accuracy

94.25%

98.40%

Radial using GRCh38 and longest ORF

  Sensitivity

98.37%

97.63%

  Specificity

97.76%

97.58%

  Accuracy

98.06%

97.61%

Quadratic using GRCh38 and first ORF

  Sensitivity

80.43%

98.66%

  Specificity

98.84%

96.78%

  Accuracy

89.63%

97.72%

Quadratic using GRCh38 and longest ORF

  Sensitivity

94.77%

95.08%

  Specificity

97.66%

97.50%

  Accuracy

96.21%

96.29%

  1. We trained 8 models with two data sets, GRCh37 and GRCh38, to select the first, or the longest, ORF relative lengths (the length of the corresponding ORF divided by the length of the transcript). The better results for each data set are in bold