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Table 2 Rate and MSE obtained by running the algorithm proposed in [39] on the PhiX dataset

From: QualComp: a new lossy compressor for quality scores based on rate distortion theory

LogBinning

R

MSE

 

UniBinning

R

MSE

 

Truncating

R

MSE

60

0

836.54

 

2

0.08

629.25

 

33

0.30

189.63

32

0.78

352.20

 

4

0.10

493.59

 

40

0.35

165.27

30

0.76

207.50

 

6

0.11

452.24

 

60

0.42

142.76

25

0.63

102.14

 

10

0.15

339.58

 

70

0.50

122.08

20

0.41

118.67

 

20

0.22

243.96

 

80

0.59

103.19

15

0.9

39.86

 

30

0.26

215.86

 

90

0.59

103.19

10

1.09

17.67

 

60

0.42

142.76

    

6

1.36

8.13

 

70

0.50

122.08

    

4

1.90

2.92

 

80

0.59

103.19

    

2

2.74

0.54

 

90

0.59

103.19

    
  1. MSE obtained by the LogBinning, UniBinning and Truncating schemes proposed in [39] with different parameters.
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BMC Bioinformatics

ISSN: 1471-2105

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