Table 1

Comparison of clustering methods using performance metrics

#

S. cerevisiae 1

#

S. cerevisiae 2

#

H. sapiens

#

E. coli

Clustering method

clusts

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clusts

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clusts

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clusts

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BHC-SE

13

0.68 ± 0.005

58

0.883 ± 0.003

6

0.75 ± 0.009

24

0.84 ± 0.003

BHC-C

9

0.66 ± 0.004

40

0.877 ± 0.002

2

0.55 ± 0.009

15

0.80 ± 0.003

SC-linear

7

0.60 ± 0.006

40

0.881 ± 0.002

4

0.69 ± 0.009

17

0.78 ± 0.004

SC-cubic

4

0.49 ± 0.005

22

0.852 ± 0.002

2

0.44 ± 0.010

8

0.67 ± 0.004

HCL

13*

0.53 ± 0.009

58*

0.881 ± 0.002

6*

0.66 ± 0.016

24*

0.68 ± 0.006

SSClust

13*

0.60 ± 0.008

58*

0.846 ± 0.003

6*

0.69 ± 0.015

24*

0.72 ± 0.010

CAGED

2

0.42 ± 0.042

6

0.606 ± 0.003

3

0.55 ± 0.020

2

0.47 ±0.005

MCLUST

8

0.60 ± 0.004

30

0.858 ± 0.002

6

0.75 ± 0.011

11

0.73 ± 0.004

Zhou

13*

0.60 ± 0.008

58*

0.853 ± 0.004

6*

0.75 ± 0.011

24*

0.74 ± 0.006


#

S. cerevisiae 1

#

S. cerevisiae 2

#

H. sapiens

#

E. coli

Clustering method

clusts

BHI ± stdev

clusts

BHI ± stdev

clusts

BHI ± stdev

clusts

BHI ± stdev


BHC-SE

13

0.70 ± 0.07

58

0.57 ± 0.03

6

0.62 ± 0.06

24

0.46 ± 0.06

BHC-C

9

0.73 ± 0.11

40

0.55 ± 0.03

2

0.78 ± 0.05

15

0.47 ± 0.04

SC-linear

7

0.69 ± 0.10

40

0.55 ± 0.02

4

0.66 ± 0.07

17

0.35 ± 0.03

SC-cubic

4

0.64 ± 0.02

22

0.53 ± 0.01

2

0.70 ± 0.03

8

0.32 ± 0.02

HCL

13*

0.50 ± 0.04

58*

0.56 ± 0.04

6*

0.52 ± 0.07

24*

0.44 ± 0.07

SSClust

13*

0.65 ± 0.03

58*

0.56 ± 0.02

6*

0.64 ± 0.05

24*

0.36 ± 0.03

CAGED

2

0.64 ± 0.02

6

0.52 ± 0.02

3

0.68 ± 0.04

2

0.21 ± 0.01

MCLUST

8

0.69 ± 0.02

30

0.55 ± 0.02

6

0.61 ± 0.06

11

0.47 ± 0.04

Zhou

13*

0.66 ± 0.03

58*

0.54 ± 0.02

6*

0.61 ± 0.06

24*

0.43 ± 0.07


#

S. cerevisiae 1

#

S. cerevisiae 2

#

H. sapiens

#

E. coli

Clustering method

clusts

log marginal likelihood

clusts

log marginal likelihood

clusts

log marginal likelihood

clusts

log marginal likelihood


BHC-SE

13

-3293

58

-3956

6

-633

24

-2497

BHC-C

9

-3356

40

-4294

2

-734

15

-2622


Table 1 shows the average Pearson correlation Coefficient (<a onClick="popup('http://www.biomedcentral.com/1471-2105/12/399/mathml/M28','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/12/399/mathml/M28">View MathML</a>) and BHI score of the four data sets for the different clustering algorithms. Confidence intervals represent ± one standard deviation, calculated by performing a nonparametric bootstrap. For the number of clusters in the partition (# clusts),* denotes that the number has not been optimized by the algorithm, but fixed at the number obtained for BHC with squared exponential covariance. The clustering methods are explained in the Methods Section. The table also shows the log-marginal likelihoods, log (P(y|T)), for BHC-SE and BHC-C. The best values for each data set are in bold.

Cooke et al. BMC Bioinformatics 2011 12:399   doi:10.1186/1471-2105-12-399

Open Data