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A comparison framework and guideline of clustering methods for mass cytometry data
BACKGROUND: With the expanding applications of mass cytometry in medical research, a wide variety of clustering methods, both semi-supervised and unsupervised, have been developed for data analysis. Selecting the optimal clustering method can accelerate the identification of meaningful cell populati...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929440/ https://www.ncbi.nlm.nih.gov/pubmed/31870419 http://dx.doi.org/10.1186/s13059-019-1917-7 |