metasnf: Meta Clustering with Similarity Network Fusion in R
Computation
2026-04-15 v2 Machine Learning
Abstract
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.
Keywords
Cite
@article{arxiv.2410.17976,
title = {metasnf: Meta Clustering with Similarity Network Fusion in R},
author = {Prashanth S Velayudhan and Xiaoqiao Xu and Prajkta Kallurkar and Ana Patricia Balbon and Maria T Secara and Adam Taback and Denise Sabac and Nicholas Chan and Shihao Ma and Bo Wang and Daniel Felsky and Stephanie H Ameis and Brian Cox and Colin Hawco and Lauren Erdman and Anne L Wheeler},
journal= {arXiv preprint arXiv:2410.17976},
year = {2026}
}
Comments
66 pages, 26 figures, provisionally accepted at Journal of Statistical Software