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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.