DLBCL

<p>Diffuse large B-cell lymphoma data set from the FlowCAP-I challenge.</p>

data

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) <doi: 10.1002/cyto.a.23601>.

Boris P. Hejblum

cytometree

Automated Cytometry Gating and Annotation

DLBCL function

<p>A data frame with 5524 cell events and 3 markers.</p>

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

Description

Usage

Arguments

Format