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

Given a high-dimensional dataset that typically represents a cytometry dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle so that datapoints within the hyperrectangle best correspond to the specified subset. In essence, this allows the conversion of clustering algorithms' outputs to gating strategies outputs.

Package details

AuthorEtienne Becht [cre, aut], Samuel Granjeaud [ctb]
MaintainerEtienne Becht <[email protected]>
LicenseGPL-3
Version0.8.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("hypergate")

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hypergate documentation built on Feb. 6, 2020, 5:14 p.m.