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superbiclust
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Download and install superbiclust package within the R console
Install from CRAN:
install.packages("superbiclust")
Install from Github:
library("remotes")
install_github("cran/superbiclust")
Install by package version:
library("remotes")
install_version("superbiclust", "1.2")
Attach the package and use:
library("superbiclust")
Maintained by
Tatsiana Khamiakova
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-04-23
Latest Update: 2021-05-28
Description:
Biclusters are submatrices in the data matrix which satisfy certain conditions of homogeneity. Package contains functions for generating robust biclusters with respect to the initialization parameters for a given bicluster solution contained in a bicluster set in data, the procedure is also known as ensemble biclustering. The set of biclusters is evaluated based on the similarity of its elements (the overlap), and afterwards the hierarchical tree is constructed to obtain cut-off points for the classes of robust biclusters. The result is a number of robust (or super) biclusters with none or low overlap.
How to cite:
Tatsiana Khamiakova (2013). superbiclust: Generating Robust Biclusters from a Bicluster Set (Ensemble Biclustering). R package version 1.2, https://cran.r-project.org/web/packages/superbiclust
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Functions, R codes and Examples using
the superbiclust R package
Some associated functions: BiclustSet-class . BiclustSet-methods . HCLtree . biclustSim-package . combine . getStats . jaccardMat . kulczynskiMat . ochiaiMat . plotProfilesAcrossAllsamples . plotProfileswithinBicluster . plotSuper . plotSuperAll . sensitivityMat . similarity . sorensenMat . specificityMat .
Some associated R codes: HCLtree.R . biclustData-class.R . getStats.R . plotTree.R . similarity.R . Full superbiclust package functions and examples
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