Co-clustering of single-cell RNA-seq data based on weighted non-negative matrix tri-factorization combined with consensus clustering
Author:
Affiliation:
1. Harbin Institute of Technology,School of Computer Science and Technology,Harbin,China
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385799.pdf?arnumber=10385799
Reference39 articles.
1. The Tumor Microenvironment Innately Modulates Cancer Progression
2. Current best practices in single‐cell RNA‐seq analysis: a tutorial
3. Review of single-cell RNA-seq data clustering for cell-type identification and characterization
4. CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data
5. scESI: evolutionary sparse imputation for single-cell transcriptomes from nearest neighbor cells
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