SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization.

ABSTRACT: Single-cell RNA-sequencing is a rapidly evolving technology that enables us to understand biological processes at unprecedented resolution. Single-cell expression analysis requires a complex data processing pipeline, and the pipeline is divided into two main parts: The quantification part, which converts the sequence information into gene-cell matrix data; the analysis part, which analyzes the matrix data using statistics and/or machine learning techniques. In the analysis part, unsupervised cell clustering plays an important role in identifying cell types and discovering cell diversity and subpopulations. Identified cell clusters are also used for subsequent analysis, such as finding differentially expressed genes and inferring cell trajectories. However, single-cell clustering using gene

SUBMITTER: Shiga M 

PROVIDER: S-EPMC8404576 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature