Microbiome datasets are often comprised of different representations or views which provide complementary information, such as genes, functions, and taxonomic assignments. Integration of multi-view information for clustering microbiome samples could create a comprehensive view of a given microbiome study. Similarity network fusion (SNF) can efficiently integrate similarities built from each view of data into a unique network that represents the full spectrum of the underlying data. Based on this method, we develop a Robust Similarity Network Fu...
