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Summary: Grouping patients into subtypes with homogeneous molecular features can guide diagnosis and therapeutic interventions. SUMO is a computational pipeline that uses nonnegative matrix factorization of patient-similarity networks to integrate continuous multi-omic datasets for molecular subtyping of a disease. Here, we present a detailed protocol to demonstrate its use in determining subtypes of lower-grade gliomas by integrating gene expression, DNA methylation, and miRNA expression data from the TCGA-LGG cohort.For complete details on the use and execution of this profile, please refer to Sienkiewicz et al. (2022).