hypergate: hypergate

In ebecht/hypergate: Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry

hypergate

Description

Finds a hyperrectangle gating around a population of interest

Usage

hypergate(xp, gate_vector, level, delta_add = 0, beta = 1, verbose = FALSE)

Arguments

xp	an Expression matrix
gate_vector	A Categorical vector of length nrow(xp)
level	A level of gate_vector so that gate_vector == level will produce a boolean vector identifying events of interest
delta_add	If the increase in F after an optimization loop is lower than delta_add, the optimization will stop (may save computation time)
beta	Purity / Yield trade-off
verbose	Boolean. Whether to print information about the optimization status.

See Also

channels_contributions for ranking parameters within the output, reoptimize_strategy for reoptimizing a output on a subset of the markers, plot_gating_strategy for plotting an output, subset_matrix_hg to apply the output to another input matrix, boolmat to obtain a boolean matrix stating which events are filtered out because of which markers

Examples

data(Samusik_01_subset)
xp=Samusik_01_subset$xp_src[,Samusik_01_subset$regular_channels]
gate_vector=Samusik_01_subset$labels
hg=hypergate(xp=xp,gate_vector=gate_vector,level=23,delta_add=0.01)

ebecht/hypergate documentation built on Feb. 4, 2024, 3:29 p.m.