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Table 1 Gene prediction performance on simulated shotgun sequences.

From: Gene prediction in metagenomic fragments based on the SVM algorithm

Methods   1200 bp    870 bp    535 bp    120 bp  
  Sn(%) Sp(%) Hm(%) Sn(%) Sp(%) Hm(%) Sn(%) Sp(%) Hm(%) Sn(%) Sp(%) Hm(%)
MG 97.7 94.8 96.3 97.4 95.2 96.3 96.9 95.4 96.1 93.2 89.6 91.4
MGC 98.0 95.2 96.6 97.7 95.5 96.6 97.2 95.7 96.4 93.3 90.0 91.6
MP 97.5 93.6 95.5 97.2 93.5 95.3 96.8 92.9 94.8 92.0 85.5 88.7
GLM 98.1 93.3 95.6 97.9 93.3 95.6 97.7 93.1 95.3 94.7 88.7 91.6
MGM 97.5 92.7 95.1 97.1 92.9 94.9 96.7 92.8 94.7 90.1 89.1 89.6
MGA 97.4 91.7 94.4 97.2 91.4 94.2 96.8 90.5 93.5 91.3 83.7 87.4
FGS 95.7 87.3 91.3 95.5 88.0 91.6 95.2 88.4 91.6 90.4 82.1 86.1
Net 94.6 94.7 94.6 94.1 94.7 94.4 93.3 94.6 93.9 82.0 76.4 79.1
  1. The gene prediction methods are denoted by abbreviations. MG: MetaGUN, MGC: complete version of MetaGUN that trained on all 261 training genomes, MP: MetaProdigal, GLM: Glimmer-MG, MGM: MetaGeneMark, FGS: FragGeneScan, MGA: MetaGeneAnnotator, Net: Orphelia.