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hypergate  

Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry
View on CRAN: Click here


Download and install hypergate package within the R console
Install from CRAN:
install.packages("hypergate")

Install from Github:
library("remotes")
install_github("cran/hypergate")

Install by package version:
library("remotes")
install_version("hypergate", "0.8.5")



Attach the package and use:
library("hypergate")
Maintained by
Etienne Becht
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-05-14
Latest Update: 2024-01-16
Description:
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.
How to cite:
Etienne Becht (2018). hypergate: Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry. R package version 0.8.5, https://cran.r-project.org/web/packages/hypergate. Accessed 21 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:48), 0.7 (2018-05-14 12:45), 0.8.1 (2019-04-17 23:20), 0.8.3 (2020-02-06 10:20), 0.8.4 (2023-08-31 15:00), 0.8 (2018-08-31 10:09)
Other packages that cited hypergate R package
View hypergate citation profile
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Complete documentation for hypergate
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