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...

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Detalles Bibliográficos
Autores principales: Ye, Xiucai, Zhang, Weihang, Futamura, Yasunori, Sakurai, Tetsuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563496/
https://www.ncbi.nlm.nih.gov/pubmed/32825786
http://dx.doi.org/10.3390/cells9091938

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563496/
https://www.ncbi.nlm.nih.gov/pubmed/32825786
http://dx.doi.org/10.3390/cells9091938

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