Clustering of single-cell multi-omics data with a multimodal deep learning method

HIGHLIGHTS

• who: Xiang Lin from the (UNIVERSITY) have published the research: Clustering of single-cell multi-omics data with a multimodal deep learning method, in the Journal: (JOURNAL) of 28/06/2021
• what: The authors develop a novel multimodal deep learning method, scMDC, for single-cell multi-omics data clustering analysis. scMDC is an end-to-end deep model that explicitly characterizes different data sources and jointly learns latent features of deep embedding for clustering analysis. The authors compare scMDC with four competing methods: Cobolt, scMM, SeuratV4, and K-means + PCA. For multi-batch data, the . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.