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

Last updated: November 26,2024

Deprecated! Installation of this package may no longer be supported.

1. Install "r-bioc-bitseq" package

Learn how to install r-bioc-bitseq on Kali Linux


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

This tutorial shows how to uninstall r-bioc-bitseq on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-bioc-bitseq
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-bioc-bitseq
Version: 1.40.0+dfsg-1
Installed-Size: 5995
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-base-core (>= 4.2.0-1), r-api-4.0, r-api-bioc-3.15, r-bioc-rsamtools (>= 1.99.3), r-bioc-s4vectors, r-bioc-iranges, r-bioc-rhtslib (>= 1.15.5), libc6 (>= 2.33), libcurl4 (>= 7.18.0), libgcc-s1 (>= 3.0), libgomp1 (>= 6), libstdc++6 (>= 11)
Suggests: r-bioc-biocstyle
Size: 1130880
SHA256: f1d36227e3b0084ff0ff07e076ebcf2b7bf5c98b4f3e10a351c371e5e7e2febc
SHA1: 24f911c55271971a590b3fe556b16d48fe078efb
MD5sum: 209b544da1a80e3a441c1a24cc824309
Description: transcript expression inference and analysis for RNA-seq data
The BitSeq package is targeted for transcript expression
analysis and differential expression analysis of RNA-seq data
in two stage process. In the first stage it uses Bayesian
inference methodology to infer expression of individual
transcripts from individual RNA-seq experiments. The second
stage of BitSeq embraces the differential expression analysis
of transcript expression. Providing expression estimates from
replicates of multiple conditions, Log-Normal model of the
estimates is used for inferring the condition mean transcript
expression and ranking the transcripts based on the likelihood
of differential expression.
Description-md5: 22ff866a439a9bfddee6c325ea799b9b
Homepage: https://bioconductor.org/packages/BitSeq/
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-bioc-bitseq/r-bioc-bitseq_1.40.0+dfsg-1_amd64.deb