Automated Cytometry Gating and Annotation

Given the hypothesis of a bi-modal distribution of cells for each marker, the algorithm constructs a binary tree, the nodes of which are subpopulations of cells. At each node, observed cells and markers are modeled by both a family of normal distributions and a family of bi-modal normal mixture distributions. Splitting is done according to a normalized difference of AIC between the two families. Method is detailed in: Commenges, Alkhassim, Gottardo, Hejblum & Thiebaut (2018) .

Overview

cytometree is a package which performs automatic gating and annotation of flow-cytometry data. On top of the CRAN help files, we also provide a vignette illustrating the functionalities of cytometree.

The cytometree algorithm rely on the construction of a binary tree, the nodes of which represents cellular (sub)populations. At each node, observed cellular markers are modeled by both a family of normal and a family of normal mixture distributions and splitting of cells into further subpopulations is decided according to a normalized difference of AIC between the two families.

Given the unsupervised nature of such a binary tree, some of the available markers may not be used to find the different cell populations present in a given sample. So in order to recover a complete annotation, we propose a post processing annotation procedure which allows the user to distinguish two or three expression levels per marker.

The following article explains in more details how cytometree works:

cytometree: a binary tree algorithm for automatic gating in cytometry analysis, Cytometry: Part A, (in press), 2018.

Installation

The easiest way to get cytometree is to install it from CRAN:

install.packages("cytometree")

Or to get the development version from GitHub:

#install.packages("devtools")
devtools::install_github("sistm/cytometree")

– Chariff Alkhassim & Boris Hejblum