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hierBipartite
View on CRAN: Click
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Download and install hierBipartite package within the R console
Install from CRAN:
install.packages("hierBipartite")
Install from Github:
library("remotes")
install_github("cran/hierBipartite") Install by package version:
library("remotes")
install_version("hierBipartite", "0.0.2") Attach the package and use:
library("hierBipartite")
Maintained by
Calvin Chi
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-16
Latest Update: 2021-02-16
Description:
Bipartite graph-based hierarchical clustering, developed for pharmacogenomic
datasets and datasets sharing the same data structure. The goal is to
construct a hierarchical clustering of groups of samples based on
association patterns between two sets of variables. In the context of
pharmacogenomic datasets, the samples are cell lines, and the two sets of
variables are typically expression levels and drug sensitivity values.
For this method, sparse canonical correlation analysis from
Lee, W., Lee, D., Lee, Y. and Pawitan, Y. (2011)
is first applied to extract association patterns for each group of samples.
Then, a nuclear norm-based dissimilarity measure is used to construct a
dissimilarity matrix between groups based on the extracted associations.
Finally, hierarchical clustering is applied.
How to cite:
Calvin Chi (2021). hierBipartite: Bipartite Graph-Based Hierarchical Clustering. R package version 0.0.2, https://cran.r-project.org/web/packages/hierBipartite. Accessed 13 Mar. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for hierBipartite
Functions, R codes and Examples using
the hierBipartite R package
Some associated functions: constructBipartiteGraph . ctrp2 . getMergeGroupRows . getSignificantMergedGroups . hierBipartite . matrixDissimilarity . newMergedGroup . null_distri . p_value . scale_features . scca .
Some associated R codes: HierBipartite.R . data.R . scca.R . utils.R . Full hierBipartite package functions and examples
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