Single-Cell RNA-Sequencing Data Clustering via Locality Preserving Kernel Matrix Alignment

Single-Cell RNA-Sequencing Data Clustering via Locality Preserving Kernel Matrix Alignment

Single-cell RNA-sequencing (scRNA-seq) data provide opportunities to reveal new insights into many biological problems such as elucidating cell types. An effective approach to elucidate cell types in complex tissues is to partition the cells into several separated subgroups via clustering techniques...

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Bibliographic Details
Main Authors: Xiao Zheng, Jiajia Chen, Chang Tang, Suqin Zhou
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
scRNA-seq clustering
elucidating cell types
tissues
similarity kernel matrices
locality preservation
Online Access:https://ieeexplore.ieee.org/document/9249423/

Internet

https://ieeexplore.ieee.org/document/9249423/

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