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

Last updated: December 25,2024

1. Install "r-bioc-sparsearray" package

This guide let you learn how to install r-bioc-sparsearray on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                r-bioc-sparsearray
            
                    
    
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2. Uninstall "r-bioc-sparsearray" package

In this section, we are going to explain the necessary steps to uninstall r-bioc-sparsearray on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-bioc-sparsearray
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-bioc-sparsearray
Version: 1.2.4+dfsg-1
Installed-Size: 2127
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-api-bioc-3.18, r-cran-matrix, r-bioc-biocgenerics (>= 0.43.1), r-bioc-matrixgenerics (>= 1.11.1), r-bioc-s4vectors, r-bioc-s4arrays (>= 1.1.6), r-cran-matrixstats, r-bioc-iranges, r-bioc-xvector, libc6 (>= 2.14)
Suggests: r-bioc-delayedarray, r-cran-testthat, r-cran-knitr, r-cran-rmarkdown, r-bioc-biocstyle
Size: 1195624
SHA256: a7c468c1aa9441f87cd3e3fad1796dabd9fe9ddabbd6aca388c550060809e747
SHA1: f00ae998e4be7fd31911c61c247475cc938fc37b
MD5sum: 55968ff9094234dc7a4768652b2dedcf
Description: efficient in-memory representation of multidimensional sparse arrays
The SparseArray package is an infrastructure package that
provides an array-like container for efficient in-memory representation
of multidimensional sparse data in R. The package defines the
SparseArray virtual class and two concrete subclasses: COO_SparseArray
and SVT_SparseArray. Each subclass uses its own internal representation
of the nonzero multidimensional data, the "COO layout" and the "SVT
layout", respectively. SVT_SparseArray objects mimic as much as
possible the behavior of ordinary matrix and array objects in base R.
In particular, they support most of the "standard matrix and array API"
defined in base R and in the matrixStats package from CRAN.
Description-md5:
Homepage: https://bioconductor.org/packages/SparseArray/
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-bioc-sparsearray/r-bioc-sparsearray_1.2.4+dfsg-1_amd64.deb