A given partitioning clustering algorithm is run repeatedly on bootstrapped data, the cluster centers then merged by hierarchical cluster algorithm. This is good for noisy data / small sample size.
From R library e1071, function bclust
R Doc Link
Also here's an online powerpoint that demonstrates the application on simulated metabolomics data:
Bagged K-means Metabolomics PPT
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