How to Install and Uninstall bolt-lmm Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: December 23,2024

1. Install "bolt-lmm" package

Please follow the guidelines below to install bolt-lmm on Ubuntu 21.04 (Hirsute Hippo)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                bolt-lmm
            
                    
    
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2. Uninstall "bolt-lmm" package

Please follow the guidance below to uninstall bolt-lmm on Ubuntu 21.04 (Hirsute Hippo):


    
        
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                sudo apt remove
            
                        
                bolt-lmm
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the bolt-lmm package on Ubuntu 21.04 (Hirsute Hippo)

Package: bolt-lmm
Architecture: amd64
Version: 2.3.4+dfsg-3
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: 940
Depends: libboost-iostreams1.74.0 (>= 1.74.0), libboost-program-options1.74.0 (>= 1.74.0), 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-3_amd64.deb
Size: 332136
MD5sum: 1638a3a614250dc5adde15f07a69563b
SHA1: 18c0ec4caff37799e90d17d00caecd367230a27b
SHA256: 005b4dc2afda23960da8bde9413304b9ce01814bcc20cded5bf2dc5ee9c5e4a5
SHA512: 120909f345144732940d310f9ed957b1f8806836978dbc8b619e2b462b6ea73adec47d65e184f7511e591c3a250e0a74ea6f0166177ba6018e1ee13ce84b645d
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.
.
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