How to Install and Uninstall bolt-lmm Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: November 07,2024

1. Install "bolt-lmm" package

Please follow the step by step instructions below to install bolt-lmm on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                bolt-lmm
            
                    
    
    Copied

2. Uninstall "bolt-lmm" package

Please follow the guidance below to uninstall bolt-lmm on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                bolt-lmm
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the bolt-lmm package on Ubuntu 20.10 (Groovy Gorilla)

Package: bolt-lmm
Architecture: amd64
Version: 2.3.4+dfsg-2build1
Priority: optional
Section: universe/science
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1044
Depends: libboost-iostreams1.71.0, libboost-program-options1.71.0, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 4.9), libnlopt0 (>= 2.6.1), libopenblas0, libstdc++6 (>= 9), zlib1g (>= 1:1.1.4)
Suggests: bolt-lmm-doc
Filename: pool/universe/b/bolt-lmm/bolt-lmm_2.3.4+dfsg-2build1_amd64.deb
Size: 360920
MD5sum: 68d5edbd70de9475045821cedd7575bd
SHA1: 380c765e89d2791630e88c5a84b43d1cba387ca2
SHA256: 51c9be11fa23265aa783c825d1b2c13101947315cc374f851f4125d2f2d46a50
SHA512: 645636d5e0de8384c3ba286eb18c664d855f7f103ee3fd75da77a4823efd25944d0f0ba8a2c055901e84524910985f84109ff5a51cb7a77f97ca27379ff11817
Homepage: https://data.broadinstitute.org/alkesgroup/BOLT-LMM/
Description-en: Efficient large cohorts genome-wide Bayesian mixed-model association testing
The BOLT-LMM software package currently consists of two main algorithms, the
BOLT-LMM algorithm for mixed model association testing, and the BOLT-REML
algorithm for variance components analysis (i.e., partitioning of
SNP-heritability and estimation of genetic correlations).
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The BOLT-LMM algorithm computes statistics for testing association between
phenotype and genotypes using a linear mixed model. By default, BOLT-LMM
assumes a Bayesian mixture-of-normals prior for the random effect attributed
to SNPs other than the one being tested. This model generalizes the standard
infinitesimal mixed model used by previous mixed model association methods,
providing an opportunity for increased power to detect associations while
controlling false positives. Additionally, BOLT-LMM applies algorithmic
advances to compute mixed model association statistics much faster than
eigendecomposition-based methods, both when using the Bayesian mixture model
and when specialized to standard mixed model association.
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The BOLT-REML algorithm estimates heritability explained by genotyped SNPs and
genetic correlations among multiple traits measured on the same set of
individuals. BOLT-REML applies variance components analysis to perform these
tasks, supporting both multi-component modeling to partition SNP-heritability
and multi-trait modeling to estimate correlations. BOLT-REML applies a Monte
Carlo algorithm that is much faster than eigendecomposition-based methods for
variance components analysis at large sample sizes.
Description-md5: 4f9ee43ad946ed850a9146b123a35ba8