Table 6

Main features of the four large scale data sets and clustering performances of the algorithms when applied to them

Dataset

Nb nodes

Nb edges

Mean degree

Mean clust coeff

MCL

MCODE

RNSC

SPC


real

permuted

real

permuted

real

permuted

real

permuted


Uetz et al. [1]

926

865

1.175

0.018

Number of clusters

288

10

48

234

Mean nb prot/cluster

3.22

11.2

1.91

3.96

Median nb prot/cluster

3

4.5

2

2

Largest cluster size

16

53

6

276

Sn

57.3%

38.6%

84.3%

74.5%

49.4%

36.5%

65.5%

43.3%

PPV

53.8%

45.9%

25.5%

21.6%

59.6%

54.4%

38.0%

38.9%

Accg

55.6%

42.3%

54.9%

48.0%

54.5%

45.5%

51.8%

41.1%

Sepco

23.0%

20.6%

48.9%

62.5%

15.5%

14.8%

19.1%

21.2%

Sepcl

30.1%

26.9%

2.2%

2.8%

34.3%

32.7%

20.3%

22.6%

Sep

26.3%

23.5%

10.4%

13.3%

23.1%

22.0%

19.7%

21.9%


Ito et al. [2]

2937

4038

2.682

0.019

Number of clusters

630

9

1746

410

Mean nb prot/cluster

4.66

97.8

1.68

7.16

Median nb prot/cluster

3

11

2

2

Largest cluster size

157

485

4

1928

Sn

34.9%

26.0%

66.9%

68.0%

31.4%

24.0%

73.2%

64.6%

PPV

42.7%

38.5%

8.2%

5.8%

63.6%

61.8%

24.3%

23.8%

Accg

38.8%

32.2%

37.5%

36.9%

47.5%

42.9%

48.8%

44.2%

Sepco

12.7%

11.8%

41.6%

33.0%

7.1%

7.0%

11.3%

11.0%

Sepcl

36.2%

33.9%

1.7%

1.3%

56.7%

55.9%

20.1%

20.4%

Sep

21.4%

20%

8.4%

6.7%

20.1%

19.8%

15.4%

15.0%


Ho et al. [5]

1564

3600

4.6

0.029

Number of clusters

314

13

957

63

Mean nb prot/cluster

4.98

49.5

1.63

24.8

Median nb prot/cluster

3

13

1

3

Largest cluster size

34

432

8

1383

Sn

50.6%

28.2%

81.2%

76.5%

37.0%

27.4%

90.1%

92.1%

PPV

47.1%

35.6%

12.9%

8.5%

61.5%

57.1%

10.4%

8.2%

Accg

48.9%

31.9%

47.1%

42.5%

49.3%

42.2%

50.2%

50.2%

Sepco

22.6%

19%

44.7%

37.2%

11%

10.5%

19.3%

13.8%

Sepcl

32.3%

27.1%

2.6%

2.2%

48%

45.6%

5.5%

4.0%

Sep

27.0%

22.7%

10.9%

9.0%

23%

21.9%

10.3%

7.4%


Gavin et al. [4]

1352

3210

4.7

0.148

Number of clusters

212

27

709

87

Mean nb prot/cluster

6.38

32.5

1.91

15.5

Median nb prot/cluster

4

7

1

2

Largest cluster size

54

414

16

1074

Sn

74.1%

24.2%

67.0%

51.1%

52.1%

20.8%

91.8%

81.4%

PPV

57.0%

23.9%

20.4%

9.4%

62.0%

46.0%

18.1%

10.7%

Accg

65.6%

24.0%

43.7%

30.3%

57.1%

33.4%

54.9%

46.0%

Sepco

39.4%

17.6%

44.5%

16.1%

14.5%

11.3%

34.4%

15.7%

Sepcl

38.0%

17.0%

5.5%

2.0%

46.9%

36.5%

13.6%

6.2%

Sep

38.7%

17.3%

15.6%

5.6%

26.1%

20.3%

21.6%

9.8%


Gavin et al. [6]

1430

6531

9.1

0.348

Number of clusters

189

39

487

136

Mean nb prot/cluster

7.57

40.3

2.94

10.5

Median nb prot/cluster

4

9

2

3

Largest cluster size

90

697

35

620

Sn

75.7%

23.7%

58.3%

43.2%

60.8%

20.9%

79.8%

48.4%

PPV

54.3%

21.0%

20.6%

8.0%

63.3%

37.3%

37.0%

16.5%

Accg

65.0%

22.4%

39.5%

25.6%

62.1%

29.1%

58.4%

32.4%

Sepco

38.1%

15.5%

44.7%

15.3%

20.1%

12.9%

34.9%

14.9%

Sepcl

32.7%

13.3%

7.9%

2.7%

44.5%

28.6%

21.6%

9.2%

Sep

35.3%

14.4%

18.8%

6.4%

29.9%

19.2%

27.4%

11.7%


Krogan et al. [7]

2675

7088

5.296

0.146

Number of clusters

813

70

1405

114

Mean nb prot/cluster

4.93

28.3

2.1

10.3

Median nb prot/cluster

3

5.5

2

3

Largest cluster size

50

387

21

1724

Sn

62.8%

19.8%

56.3%

30.9%

53.1%

19.1%

82.6%

64.0%

PPV

56.2%

33.5%

21.9%

9.7%

63.3%

51.1%

25.4%

17.2%

Accg

59.5%

26.7%

39.1%

20.3%

58.2%

35.1%

54.0%

40.6%

Sepco

20.0%

12.1%

33.2%

13.6%

10.3%

8.7%

20.3%

11.9%

Sepcl

49.5%

29.9%

8.8%

3.6%

59.6%

50.3%

24.0%

14.1%

Sep

31.5%

19.0%

17.0%

7.0%

24.7%

21.6%

20.9%

12.9%


Brohée and van Helden BMC Bioinformatics 2006 7:488   doi:10.1186/1471-2105-7-488

Open Data