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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
PeerJ Inc.
2023
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| Materias: | |
| 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 |