A metagene based similarity network fusion approach for multi-omics data integration identified novel subtypes in renal cell carcinoma.

ABSTRACT: Renal cell carcinoma (RCC) ranks among the most prevalent cancers worldwide, with both incidence and mortality rates increasing annually. The heterogeneity among RCC patients presents considerable challenges for developing universally effective treatment strategies, emphasizing the necessity of in-depth research into RCC's molecular mechanisms, understanding the variations among RCC patients and further identifying distinct molecular subtypes for precise treatment. We proposed a metagene-based similarity network fusion (Meta-SNF) method for RCC subtype identification with multi-omics data, using a non-negative matrix factorization technique to capture alternative structures inherent in the dataset as metagenes. These latent metagenes were then integrated to construct a fused network under

SUBMITTER: Jia C 

PROVIDER: S-EPMC11576078 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature