Non-negative low-rank representation based on dictionary learning for single-cell RNA-sequencing data analysis

In the analysis of single-cell RNA-sequencing (scRNA-seq) data, how to effectively and accurately identify cell clusters from a large number of cell mixtures is still a challenge. Low-rank representation (LRR) method has achieved excellent results in subspace clustering. But in previous studies, mos...

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Detalles Bibliográficos
Autores principales: Wang, Juan, Zhang, Nana, Yuan, Shasha, Shang, Junliang, Dai, Lingyun, Li, Feng, Liu, Jinxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9789616/
https://www.ncbi.nlm.nih.gov/pubmed/36564711
http://dx.doi.org/10.1186/s12864-022-09027-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9789616/
https://www.ncbi.nlm.nih.gov/pubmed/36564711
http://dx.doi.org/10.1186/s12864-022-09027-0

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