scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

Abstract Background Single-cell RNA sequencing (scRNA-seq) strives to capture cellular diversity with higher resolution than bulk RNA sequencing. Clustering analysis is critical to transcriptome research as it allows for further identification and discovery of new cell types. Unsupervised clustering...

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Bibliographic Details
Main Authors: Zile Wang, Haiyun Wang, Jianping Zhao, Chunhou Zheng
Format: Article
Language:English
Published: BMC 2023-05-01
Series:BMC Bioinformatics
Subjects:
Deep learning
scRNA-seq
Semi-supervised
Clustering
Adversarial autoencoder
Online Access:https://doi.org/10.1186/s12859-023-05339-4

Internet

https://doi.org/10.1186/s12859-023-05339-4

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