Learn R Programming

cytometree

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:

Commenges D, Alkhassim C, Gottardo R, Hejblum BP, Thiébaut R (2018). cytometree: a binary tree algorithm for automatic gating in cytometry analysis. Cytometry Part A 93(11):1132-1140. <doi: 10.1002/cyto.a.23601>

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

Copy Link

Version

Install

install.packages('cytometree')

Monthly Downloads

270

Version

2.0.2

License

LGPL-3 | file LICENSE

Maintainer

Boris P. Hejblum

Last Published

December 4th, 2019

Functions in cytometree (2.0.2)

GaussMix

Bi-modal normal mixture distribution.
Log10Transformation

Data transformation using log10
plot_cytopop

Plot the cell count for each population using CytomeTree.
plot_graph

Plot the binary tree built using CytomeTree.
LeavesMedians

Computes medians of leaves given cytomeTreeObj.
FmeasureC

C++ implementation of the F-measure computation
Partition2gr

Computes N-1 possible partitions of ordered N into 2 subsets.
FmeasureC_no0

C++ implementation of the F-measure computation without the reference class labeled "0"
Partition3gr

Computes (N-1)*(N-2) possible partitions of N into 3 subsets.
HIPC

HIPC T cell data set from HIPC program, patient 12828. The data was analyzed and gated by Stanford.
IMdata

Influenza vaccine response dataset
plot_nodes

Plot the distribution of the observed cells at each node of the binary tree built using CytomeTree.
AsinhTransformation

Data transformation using asinh
KmeansOPT

Finds the partition which minimize the within-leaves sum of squares.
LeavesCenters

Computes means of leaves given cytomeTreeObj.
TreeAnnot

Returns the underlying annotation given a tree pattern.
RetrievePops

Retrieve cell populations found using Annotation.
bootstrapCI

Bootstrapped Confidence Interval.
cytometree-package

Binary tree algorithm for cytometry data analysis.
GaussMix2

tri-modal normal mixture distribution.
Annotation

Annotates cell populations found using CytomeTree.
CytofTree

Binary tree algorithm for mass cytometry data analysis.
CytomeTree

Binary tree algorithm for cytometry data analysis.
Cytof_BinaryTree

Builds a binary tree for mass cytometry data.
BinaryTree

Builds a binary tree.
BiexpTransformation

Data transformation using biexp
CytofEM

E-M algorithm for cytoftree.
CytEM

E-M algorithm.
DLBCL

Diffuse large B-cell lymphoma data set from the FlowCAP-I challenge.