Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data
Abstract 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...
Tallennettuna:
| Päätekijät: | , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
BMC
2022-02-01
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| Sarja: | Genome Biology |
| Linkit: | https://doi.org/10.1186/s13059-022-02622-0 |
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