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ClustAll: Data driven strategy to find groups of patients within complex diseases

Bioconductor version: Release (3.19)

Data driven strategy to find hidden groups of patients with complex diseases using clinical data. ClustAll facilitates the unsupervised identification of multiple robust stratifications. ClustAll, is able to overcome the most common limitations found when dealing with clinical data (missing values, correlated data, mixed data types).

Author: Asier Ortega-Legarreta [aut, cre] , Sara Palomino-Echeverria [aut]

Maintainer: Asier Ortega-Legarreta <aortegal at>

Citation (from within R, enter citation("ClustAll")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

ClustALL User's Guide HTML R Script
Reference Manual PDF


biocViews Clustering, DimensionReduction, PrincipalComponent, Software, StatisticalMethod
Version 1.0.0
In Bioconductor since BioC 3.19 (R-4.4) (< 6 months)
License GPL-2
Depends R (>= 4.2.0)
Imports FactoMineR, bigstatsr, clValid, doSNOW, parallel, foreach, dplyr, fpc, mice, modeest, flock, networkD3, methods, ComplexHeatmap, cluster, RColorBrewer, circlize, grDevices, ggplot2, grid, stats, utils, pbapply
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Suggests RUnit, knitr, BiocGenerics, rmarkdown, BiocStyle, roxygen2
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Follow Installation instructions to use this package in your R session.

Source Package ClustAll_1.0.0.tar.gz
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macOS Binary (x86_64) ClustAll_1.0.0.tgz
macOS Binary (arm64) ClustAll_1.0.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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