Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning

Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning

High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes causing cell-to-cell variability for understanding...

Full description

Bibliographic Details
Main Authors: Xiucai Ye, Weihang Zhang, Yasunori Futamura, Tetsuya Sakurai
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Cells
Subjects:
single-cell RNA-seq
machine learning
interactive gene groups
co-expression networks
subgraph learning
Online Access:https://www.mdpi.com/2073-4409/9/9/1938

Internet

https://www.mdpi.com/2073-4409/9/9/1938

Similar Items