Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements

Cooke, Emma J; Savage, Richard S; Kirk, Paul DW; Darkins, Robert; Wild, David L

doi:10.1186/1471-2105-12-399

BMC Bioinformatics

Table 1 Comparison of clustering methods using performance metrics

From: Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements

	#	*S. cerevisiae 1*	#	*S. cerevisiae 2*	#	*H. sapiens*	#	*E. coli*
Clustering method	clusts	$P \bar{C} C \pm stdev$	clusts	$P \bar{C} C \pm stdev$	clusts	$P \bar{C} C \pm stdev$	clusts	$P \bar{C} C \pm stdev$
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 ( $P \bar{C} C$ ) 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.

Back to article page

ISSN: 1471-2105

Contact us

General enquiries: journalsubmissions@springernature.com