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

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. This enables researchers to efficiently integrate advanced clustering methodologies into their analysis pipelines