metasnf: Meta Clustering with Similarity Network Fusion in R
This is an incremental tool for biomedical researchers using SNF for subtype discovery, enabling more efficient and context-guided clustering.
The authors tackled the problem of efficiently searching a broad space of cluster solutions in similarity network fusion (SNF) workflows by developing metasnf, an R package that applies meta clustering to cluster the solutions themselves, resulting in a tool that helps researchers identify context-specific cluster solutions.
metasnf is an R package that enables users to apply meta clustering, a method for efficiently searching a broad space of cluster solutions by clustering the solutions themselves, to clustering workflows based on similarity network fusion (SNF). SNF is a multi-modal data integration algorithm commonly used for biomedical subtype discovery. The package also contains functions to assist with cluster visualization, characterization, and validation. This package can help researchers identify SNF-derived cluster solutions that are guided by context-specific utility over context-agnostic measures of quality.