Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.
Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
STAR Protoc. 2022 Jan 19;3(1):101110. doi: 10.1016/j.xpro.2021.101110. eCollection 2022 Mar 18.
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).
将患者分为具有同质分子特征的亚型可以指导诊断和治疗干预。SUMO 是一个计算流程，它使用患者相似性网络的非负矩阵分解来整合连续的多组学数据集，以对疾病进行分子亚型分析。在这里，我们提供了一个详细的方案，通过整合 TCGA-LGG 队列中的基因表达、DNA 甲基化和 miRNA 表达数据，来展示其在确定低级别胶质瘤亚型中的应用。有关此配置文件的使用和执行的完整详细信息，请参阅 Sienkiewicz 等人（2022 年）。
