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bioRxiv · 10.1101/2022.11.03.515009

Ensemble Clustering Combined with Clustering Optimization: A Novel Workflow for Analyzing Metabolomics Data

Hislop, B. D.·Heveran, C. M.·June, R. K.
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Abstract

Modern biological research often leverages clustering to elucidate disease endotypes and underlying mechanisms. Mono-cluster solutions remain the predominant method; however, this approach has concerning pitfalls, motivating the need for ensemble clustering methods. We present Ensemble Clustering Combined with Cluster Optimization (ECCO), an open-source Python UI that provides a fast, scalable framework for ensemble clustering of large-scale data. It includes zero-code integration of novel ensemble clustering methods and many pre- and post-processing functionalities, enabling researchers to efficiently integrate advanced clustering methodologies into their analysis pipelines.

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Hislop, B. D., Heveran, C. M., June, R. K.. 2022-11-04. Ensemble Clustering Combined with Clustering Optimization: A Novel Workflow for Analyzing Metabolomics Data. https://doi.org/10.1101/2022.11.03.515009

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