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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
F1000 Research Limited
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134335/ https://www.ncbi.nlm.nih.gov/pubmed/30271584 http://dx.doi.org/10.12688/f1000research.15666.3 |