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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