How to Install and Uninstall r-bioc-multtest Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: January 11,2025

1. Install "r-bioc-multtest" package

This tutorial shows how to install r-bioc-multtest on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

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

This guide let you learn how to uninstall r-bioc-multtest on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-bioc-multtest
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-bioc-multtest package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-bioc-multtest
Architecture: amd64
Version: 2.44.0-1build1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1061
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-api-bioc-3.11, r-bioc-biocgenerics, r-bioc-biobase, r-cran-survival, r-cran-mass, libc6 (>= 2.29)
Suggests: r-cran-snow
Filename: pool/universe/r/r-bioc-multtest/r-bioc-multtest_2.44.0-1build1_amd64.deb
Size: 842356
MD5sum: 08914521651dbca1c6326d54ec86bae4
SHA1: 36620c1a48a4c23f5db11cc608af6fb7c8cd0583
SHA256: 935674a00172e85bc99d2fed72abb49474cc219dc6e5413d4a3a66e65c79bfd1
SHA512: 715fb0f2effd7b88eb8649795616fed18893ed36fbcb115fa9229698248d36f9000453486aa191441a95a70fa5b5cf733e48cc2d7a6480bafc562d3b4b936983
Homepage: https://bioconductor.org/packages/multtest/
Description-en: Bioconductor resampling-based multiple hypothesis testing
Non-parametric bootstrap and permutation resampling-based multiple
testing procedures (including empirical Bayes methods) for controlling
the family-wise error rate (FWER), generalized family-wise error rate
(gFWER), tail probability of the proportion of false positives (TPPFP),
and false discovery rate (FDR). Several choices of bootstrap-based null
distribution are implemented (centered, centered and scaled,
quantile-transformed). Single-step and step-wise methods are available.
Tests based on a variety of t- and F-statistics (including t-statistics
based on regression parameters from linear and survival models as well
as those based on correlation parameters) are included. When probing
hypotheses with t-statistics, users may also select a potentially faster
null distribution which is multivariate normal with mean zero and
variance covariance matrix derived from the vector influence function.
Results are reported in terms of adjusted p-values, confidence regions
and test statistic cutoffs. The procedures are directly applicable to
identifying differentially expressed genes in DNA microarray
experiments.
Description-md5: c4112391aa6882e8925f94048452c84f