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 autom...
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| Published in: | Genome Biology Vol. 23; no. 1; p. 49 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
London
BioMed Central
08.02.2022
Springer Nature B.V BMC |
| Subjects: | |
| ISSN: | 1474-760X, 1474-7596, 1474-760X |
| Online Access: | Get full text |
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