scSSA: A clustering method for single cell RNA-seq data based on semi-supervised autoencoder

•In this study, We proposed to use semi-supervised autoencoder to reduce the dimension of data, because it makes good use of some existing label information.•In Gaussian mixture clustering, we choose to use BIC index for machine parameter adjustment, which reduces the workload of manual parameter ad...

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Bibliographic Details
Published in:	Methods (San Diego, Calif.) Vol. 208; pp. 66 - 74
Main Authors:	Zhao, Jian-Ping, Hou, Tong-Shuai, Su, Yansen, Zheng, Chun-Hou
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.12.2022
Subjects:	data collection epigenome Fast independent component analysis Gaussian mixture clustering gene expression genes independent component analysis RNA scRNA-seq Semi-supervised autoencoder sequence analysis transcriptome scRNA-seq Gaussian mixture clustering Fast independent component analysis Semi-supervised autoencoder
ISSN:	1046-2023, 1095-9130, 1095-9130
Online Access:	Get full text
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