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)