R: Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry

# Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry

## Documentation for package ‘hypergate’ version 0.8.5

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

boolmat | boolmat
channels_contributions | channels_contributions
color_biplot_by_discrete | Colors a biplot according to a vector with discrete values
contract | contract
contract.update | contract.update
coreloop | coreloop
en.locator | Wrapper to locator that plots segments on the fly
expand | expand
expand.update | expand.update
f | f
fill_FNTN_matrix | fill_FNTN_matrix
FNTN_matrix.recycle | FNTN_matrix.recycle
F_beta | F_beta
gate_from_biplot | gate_from_biplot
hgate_info | hgate_info
hgate_pheno | hgate_pheno
hgate_rule | hgate_rule
hgate_sample | hgate_sample
hypergate | hypergate
plot_gating_strategy | plot_gating_strategy
polygon.clean | Remove self intersection in polygons
reoptimize_strategy | reoptimize_strategy
Samusik_01_subset | 2000 events randomly sampled from the 'Samusik_01' dataset
subset_matrix_hg | subset_matrix_hg
update_gate | Updates a gate vector