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A systematic performance evaluation of clustering methods for single-cell RNA-seq data
Subpopulation identification, usually via some form of unsupervised clustering, is a fundamental step in the analysis of many single-cell RNA-seq data sets. This has motivated the development and application of a broad range of clustering methods, based on various underlying algorithms. Here, we pro...
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| Publicado no: | F1000Res |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
F1000 Research Limited
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6134335/ https://ncbi.nlm.nih.gov/pubmed/30271584 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.12688/f1000research.15666.3 |
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