How to Install and Uninstall r-bioc-mofa Package on Kali Linux

Last updated: November 05,2024

1. Install "r-bioc-mofa" package

Please follow the guidance below to install r-bioc-mofa on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-bioc-mofa
            
                    
    
    Copied

2. Uninstall "r-bioc-mofa" package

This is a short guide on how to uninstall r-bioc-mofa on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-bioc-mofa
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-bioc-mofa package on Kali Linux

Package: r-bioc-mofa
Version: 1.6.1+dfsg-12
Installed-Size: 770
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-api-4.0, r-api-bioc-3.18, r-bioc-rhdf5, r-cran-dplyr, r-cran-reshape2, r-cran-pheatmap, r-cran-corrplot, r-cran-ggplot2, r-cran-ggbeeswarm, r-cran-scales, r-cran-ggally, r-cran-rcolorbrewer, r-cran-cowplot, r-cran-ggrepel, r-bioc-multiassayexperiment, r-bioc-biobase, r-cran-doparallel, r-cran-foreach, r-cran-reticulate, python3-mofapy
Suggests: r-cran-knitr
Size: 570760
SHA256: 106f07aa8e84735c5655020dd5f399da098701c50f6f253554e8908342099b66
SHA1: 9ce1b0fc538e67e856ffdf8e41a586c7237469c1
MD5sum: a477c16a6f078ec8bbe7d84d16a16cc4
Description: Multi-Omics Factor Analysis (MOFA)
Multi-Omics Factor Analysis: an unsupervised framework for the
integration of multi-omics data sets.
.
Upstream no longer supports this package. This package only still
ships to help with rerunning/comparing/transitioning existing projects.
For new projects please upgrade to MOFA2 (MOFA+). Actually, also when
adding new data to old projects, MOFA2 has further improved the handling
of multiple factors, and to compensate for a batch effect that is likely
introduced with additional data, may be an immediate use case for that
new version.
Description-md5:
Homepage: https://bioconductor.org/packages/MOFA/
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-bioc-mofa/r-bioc-mofa_1.6.1+dfsg-12_all.deb