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

Last updated: May 13,2024

1. Install "r-bioc-qusage" package

Here is a brief guide to show you how to install r-bioc-qusage on Kali Linux


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

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


    
        
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                sudo apt remove
            
                        
                r-bioc-qusage
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-bioc-qusage
Version: 2.36.0-1
Installed-Size: 10134
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-api-4.0, r-api-bioc-3.18, r-bioc-limma (>= 3.14), r-bioc-biobase, r-cran-nlme, r-cran-emmeans, r-cran-fftw
Size: 10036864
SHA256: e35ef484ff06c9b84e59fa598bc5c441305d500d71e1e4ea41f02fa6a28a860b
SHA1: 9270b0190de65f2b4eb43558cf43d4bd642c9214
MD5sum: 85a3c80f1d264bf1903b0e292bb99821
Description: qusage: Quantitative Set Analysis for Gene Expression
This package is an implementation the Quantitative Set
Analysis for Gene Expression (QuSAGE) method described in
(Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene
Set Enrichment-type test, which is designed to provide a
faster, more accurate, and easier to understand test for gene
expression studies. qusage accounts for inter-gene correlations
using the Variance Inflation Factor technique proposed by Wu et
al. (Nucleic Acids Res, 2012). In addition, rather than simply
evaluating the deviation from a null hypothesis with a single
number (a P value), qusage quantifies gene set activity with a
complete probability density function (PDF). From this PDF, P
values and confidence intervals can be easily extracted.
Preserving the PDF also allows for post-hoc analysis (e.g.,
pair-wise comparisons of gene set activity) while maintaining
statistical traceability. Finally, while qusage is compatible
with individual gene statistics from existing methods (e.g.,
LIMMA), a Welch-based method is implemented that is shown to
improve specificity. For questions, contact Chris Bolen
([email protected]) or Steven Kleinstein
([email protected])
Description-md5:
Homepage: https://bioconductor.org/packages/qusage/
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-bioc-qusage/r-bioc-qusage_2.36.0-1_all.deb