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Figure 7 | BMC Bioinformatics

Figure 7

From: An approach for clustering gene expression data with error information

Figure 7

Gap statistic for estimating the number of clusters. The figure shows the results of calculating the gap statistic for different numbers of clusters using the CORE algorithm for each of the four data sets. Each point along the curves represents a comparison between the within-cluster dispersion of the clustered data set, as determined by the CORE algorithm, and the average within-cluster dispersion of B = 100 samples of a clustered complete reference distribution, as determined by CORE. Generation of the reference distribution is described in the text. The error bars in the figure reflect the standard deviation of the gap statistic across the B reference distribution samples. The recommended value for the parameter k is the smallest number of clusters, i, such that the gap statistic at i is greater than or equal to the gap statistic at i+1, less the estimated error of the gap statistic at i+1. (A) For normally distributed synthetic data generated from 50 classes, the gap statistic suggests a parameter value of k = 60. (B) For periodic time series synthetic data generated from 4 classes, the gap statistic suggests a parameter value of k = 4. (C) For 904 E. coli genes belonging to 275 multi-gene operons, the gap statistic suggests a parameter value of k = 260. (D) For 205 yeast genes which have each been annotated with one of four functional classifications, the gap statistic suggests a parameter value of k = 5. For each of the four data sets, the gap statistic suggests a value for the parameter k which is close to the number of true classes in the data set.

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