A clustering method for small scRNA-seq data based on subspace and weighted distance

BACKGROUND: Identifying the cell types using unsupervised methods is essential for scRNA-seq research. However, conventional similarity measures introduce challenges to single-cell data clustering because of the high dimensional, high noise, and high dropout. METHODS: We proposed a clustering method...

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Detalles Bibliográficos
Autores principales: Ning, Zilan, Dai, Zhijun, Zhang, Hongyan, Chen, Yuan, Yuan, Zheming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879162/
https://www.ncbi.nlm.nih.gov/pubmed/36710872
http://dx.doi.org/10.7717/peerj.14706

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879162/
https://www.ncbi.nlm.nih.gov/pubmed/36710872
http://dx.doi.org/10.7717/peerj.14706

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