Cluster stability in the analysis of mass cytometry data

Deep phenotyping of Tregs identifies an immune signature for idiopathic aplastic anemia and predicts response to treatment

(2016) S. Kordasti et al.   BLOOD

Phenotypic Complexity of the Human Regulatory T Cell Compartment Revealed by Mass Cytometry

(2015) Gavin M. Mason et al.   JOURNAL OF IMMUNOLOGY

Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data

(2015) Kirsten E. Diggins et al.   METHODS

High-dimensional analysis of the murine myeloid cell system

(2014) Burkhard Becher et al.   NATURE IMMUNOLOGY

Automated identification of stratifying signatures in cellular subpopulations

(2014) Robert V. Bruggner et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Clinical recovery from surgery correlates with single-cell immune signatures

(2014) B. Gaudilliere et al.   Science Translational Medicine

viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia

(2013) El-ad David Amir et al.   NATURE BIOTECHNOLOGY

Critical assessment of automated flow cytometry data analysis techniques

(2013) Nima Aghaeepour et al.   NATURE METHODS

Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

(2011) Peng Qiu et al.   NATURE BIOTECHNOLOGY

Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum

(2011) S. C. Bendall et al.   SCIENCE

Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data

(2010) Yu Qian et al.   CYTOMETRY PART B-CLINICAL CYTOMETRY