A comparison framework and guideline of clustering methods for mass cytometry data
A comparison framework and guideline of clustering methods for mass cytometry data
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 populations.