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

Last updated: November 22,2024

1. Install "r-bioc-pcamethods" package

In this section, we are going to explain the necessary steps to install r-bioc-pcamethods on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-bioc-pcamethods
            
                    
    
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2. Uninstall "r-bioc-pcamethods" package

Please follow the instructions below to uninstall r-bioc-pcamethods on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-bioc-pcamethods
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-bioc-pcamethods
Version: 1.94.0-1
Installed-Size: 1391
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-api-bioc-3.18, r-bioc-biobase, r-bioc-biocgenerics, r-cran-rcpp (>= 0.11.3), r-cran-mass, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 13.1)
Suggests: r-cran-matrixstats, r-cran-lattice, r-cran-ggplot2
Size: 963540
SHA256: b211d3f0dc93f8e9d46dff0a506ced84116641ac67b2be0d78f0a6b49e83eb59
SHA1: d874e027d043391c2d52cd3d3459bfdfc9d92616
MD5sum: ea73b14c3ff1b4f4e720db80257340b8
Description: BioConductor collection of PCA methods
Provides Bayesian PCA, Probabilistic PCA, Nipals PCA,
Inverse Non-Linear PCA and the conventional SVD PCA. A cluster
based method for missing value estimation is included for
comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA
on incomplete data as well as for accurate missing value
estimation. A set of methods for printing and plotting the
results is also provided. All PCA methods make use of the same
data structure (pcaRes) to provide a common interface to the
PCA results. Initiated at the Max-Planck Institute for
Molecular Plant Physiology, Golm, Germany.
Description-md5:
Homepage: https://bioconductor.org/packages/pcaMethods/
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-bioc-pcamethods/r-bioc-pcamethods_1.94.0-1_amd64.deb