Science not art: statistically sound methods for identifying subsets in multi-dimensional flow and mass cytometry data sets

Nature Reviews Immunology 18, 77 (2018). doi:10.1038/nri.2017.150 Authors: Darya Y. Orlova, Leonore A. Herzenberg & Guenther Walther Automated approaches that cluster high-dimensional flow and mass cytometry data simultaneously in multiple dimensions, such as those discussed in Saeys et al. (Computational flow cytometry: helping to make sense of high-dimensional immunology data. Nat. Rev. Immunol.16, 449–462 2016), are
Source: Nature Reviews Immunology - Category: Allergy & Immunology Authors: Tags: Correspondence Source Type: research