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Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data
BACKGROUND: A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately detect the number of cell types in the sample, which can be critical for downstream analyses such as cell type identification. Various scRNA-seq data clustering algorithms have been specifically designed to auto...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822786/ https://www.ncbi.nlm.nih.gov/pubmed/35135612 http://dx.doi.org/10.1186/s13059-022-02622-0 |