A kernel non-negative matrix factorization framework for single cell clustering

DOI10.1016/j.apm.2020.08.065zbMath1481.92045OpenAlexW3088867730MaRDI QIDQ2241802

Hao Jiang, Ming Yi, Shi-Hua Zhang

Publication date: 9 November 2021

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2020.08.065

zbMATH Keywords

cellular heterogeneitykernel non-negative matrix factorizationsingle cell RNA-sequencing

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Biochemistry, molecular biology (92C40)

Uses Software

• SC3
• ZIFA
• SNN-Cliq
• BASiCS
• M3Drop

Cites Work

• A unified statistical framework for single cell and bulk RNA sequencing data
• Nonlinear nonnegative matrix factorization based on Mercer kernel construction
• Diffusion maps
• Learning the parts of objects by non-negative matrix factorization

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