Cytometree: A binary tree algorithm for automatic gating in cytometry analysis
COMMENGES, Daniel
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
ALKHASSIM, Chariff
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Leer más >
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
COMMENGES, Daniel
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
ALKHASSIM, Chariff
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
HEJBLUM, Boris![](/themes/Mirage2//images/PERSO.svg)
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
![cc](/themes/Mirage2//images/orcid_icon.png)
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
THIEBAUT, Rodolphe
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
< Leer menos
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Idioma
EN
Article de revue
Este ítem está publicado en
Cytometry Part A. 2018-11, vol. 93, n° 11, p. 1132-1140
Resumen en inglés
Flow cytometry is a powerful technology that allows the high-throughput quantification of dozens of surface and intracellular proteins at the single-cell level. It has become the most widely used technology for immunophenotyping ...Leer más >
Flow cytometry is a powerful technology that allows the high-throughput quantification of dozens of surface and intracellular proteins at the single-cell level. It has become the most widely used technology for immunophenotyping of cells over the past three decades. Due to the increasing complexity of cytometry experiments (more cells and more markers), traditional manual flow cytometry data analysis has become untenable due to its subjectivity and time-consuming nature. We present a new unsupervised algorithm called "cytometree" to perform automated population identification (aka gating) in flow cytometry. cytometree is based on the construction of a binary tree, the nodes of which are subpopulations of cells. At each node, the marker distributions are modeled by mixtures of normal distributions. Node splitting is done according to a model selection procedure based on a normalized difference of Akaike information criteria between two competing models. Post-processing of the tree structure and derived populations allows us to complete the annotation of the populations. The algorithm is shown to perform better than the state-of-the-art unsupervised algorithms previously proposed on panels introduced by the Flow Cytometry: Critical Assessment of Population Identification Methods project. The algorithm is also applied to a T-cell panel proposed by the Human Immunology Project Consortium (HIPC) program; it also outperforms the best unsupervised open-source available algorithm while requiring the shortest computation time. (c) 2018 International Society for Advancement of Cytometry.< Leer menos
Palabras clave en inglés
Biostatistics
SISTM
Centros de investigación