Package: superbiclust 1.2

superbiclust: Generating Robust Biclusters from a Bicluster Set (Ensemble Biclustering)

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.

Authors:Tatsiana Khamiakova

superbiclust_1.2.tar.gz
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superbiclust.pdf |superbiclust.html
superbiclust/json (API)

# Install 'superbiclust' in R:
install.packages('superbiclust', repos = c('https://tkhamiak.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 packages 2 scripts 456 downloads 16 exports 44 dependencies

Last updated 4 years agofrom:f0aceb7833. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 12 2025
R-4.5-winNOTEMar 12 2025
R-4.5-macNOTEMar 12 2025
R-4.5-linuxNOTEMar 12 2025
R-4.4-winNOTEMar 12 2025
R-4.4-macNOTEMar 12 2025
R-4.4-linuxNOTEMar 12 2025
R-4.3-winOKMar 12 2025
R-4.3-macOKMar 12 2025

Exports:BiclustSetcombinegetStatsHCLtreejaccardMatkulczynskiMatochiaiMatplotProfilesAcrossAllSamplesplotProfilesWithinBiclusterplotSuperplotSuperAllsensitivityMatsimilaritysorensenMatspecificityMatsummary

Dependencies:additivityTestsbiclustBiobaseBiocGenericsclassclicolorspacecpp11dplyrfabiafansifarverflexclustgenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmodeltoolsmunsellnlmepillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr