A systematic performance evaluation of clustering methods for single-cell RNA-seq data [version 2; referees: 2 approved]
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
F1000 Research Ltd
2018-09-01
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| Series: | F1000Research |
| Online Access: | https://f1000research.com/articles/7-1141/v2 |