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Table 1 Summary of quantitative analysis with MASPECTRAS, MSQuant and PepQuan

From: MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

 

10 heavy to 1 light

 

1 heavy to 10 light

 

MSQuant

PepQuan

MASPECTRAS

 

MSQuant

PepQuan

MASPECTRAS

 

auto

manual

auto

manual

 

auto

manual

auto

manual

# peptides

22

33

27

40

# peptides

20

82

28

39

mean

4.64

8.94

8.31

9.85

mean

7.54

7

9.77

9.29

stdev

4.83

4.9

2.85

2.99

stdev

4.94

2.51

3.96

1.92

CV %

104.09%

54.81%

34.30%

30.36%

CV %

65.52%

35.86%

40.53%

20.67%

ratio: heavy/light

ratio: light/heavy

 

5 heavy to 1 light

 

1 heavy to 5 light

 

MSQuant

PepQuan

MASPECTRAS

 

MSQuant

PepQuan

MASPECTRAS

 

auto

manual

auto

manual

 

auto

manual

auto

manual

# peptides

14

43

50

53

# peptides

16

67

41

40

mean

2.94

4.27

4.16

4.67

mean

13.36

3.74

4.25

4.84

stdev

2.3

1.69

1.56

1.12

stdev

5.18

1.36

1.15

0.93

CV %

78.23%

39.58%

37.50%

23.98%

CV %

38.77%

36.36%

27.06%

19.21%

ratio: heavy/light

ratio: light/heavy

 

2 heavy to 1 light

 

1 heavy to 2 light

 

MSQuant

PepQuan

MASPECTRAS

 

MSQuant

PepQuan

MASPECTRAS

 

auto

manual

auto

manual

 

auto

manual

auto

manual

# peptides

25

50

48

72

# peptides

16

74

42

47

mean

1.048

2.17

2.07

2.03

mean

4.24

2.07

2.11

1.94

stdev

1.15

0.7

0.71

0.54

stdev

4.97

3.04

0.63

0.3

CV %

109.73%

32.26%

34.30%

26.60%

CV %

117.22%

146.86%

29.86%

15.46%

ratio: heavy/light

ratio: light/heavy

 

1 heavy to 1 light

     
 

MSQuant

PepQuan

MASPECTRAS

     
 

auto

manual

auto

manual

     

# peptides

15

67

98

77

     

mean

0.92

1.28

0.97

0.99

     

stdev

0.46

0.48

0.24

0.19

     

CV %

49.30%

37.50%

24.74%

19.10%

     
  1. A filter for outlier removal has been applied to the automatically calculated ratios in MASPECTRAS. For the manual evaluation, these automatically removed peptides were checked manually and the misquantification due to wrong peak detection could be corrected. Therefore the amount of manually accepted peptides could be higher than the automatically accepted ones. The quantification with ASAPRatio integrated in MASPECTRAS performed superior compared to both, MSQuant and PepQuan. Furthermore, for all ratios the relative error calculated was considerably lower than the relative error obtained with MSQuant and PepQuan.
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BMC Bioinformatics

ISSN: 1471-2105

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