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...

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Detalles Bibliográficos
Autores principales: Liu, Xiao, Song, Weichen, Wong, Brandon Y., Zhang, Ting, Yu, Shunying, Lin, Guan Ning, Ding, Xianting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
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

Internet

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

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