Automated Cytometry Gating and Annotation
Annotates cell populations found using CytomeTree.
Data transformation using asinh
Data transformation using biexp
Builds a binary tree.
Bootstrapped Confidence Interval.
E-M algorithm.
Builds a binary tree for mass cytometry data.
E-M algorithm for cytoftree.
Binary tree algorithm for mass cytometry data analysis.
cytometree: Automated Cytometry Gating and Annotation
Binary tree algorithm for cytometry data analysis.
C++ implementation of the F-measure computation without the reference ...
C++ implementation of the F-measure computation
Bi-modal normal mixture distribution.
tri-modal normal mixture distribution.
Finds the partition which minimize the within-leaves sum of squares.
Computes means of leaves given cytomeTreeObj.
Computes medians of leaves given cytomeTreeObj.
Data transformation using log10
Computes N-1 possible partitions of ordered N into 2 subsets.
Computes (N-1)*(N-2) possible partitions of N into 3 subsets.
Plot the cell count for each population using CytomeTree.
Plot the binary tree built using CytomeTree.
Plot the distribution of the observed cells at each node of the binary...
Retrieve cell populations found using Annotation.
Returns the underlying annotation given a tree pattern.
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>.
Useful links