How to Install and Uninstall berkeley-express Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: November 07,2024

1. Install "berkeley-express" package

This is a short guide on how to install berkeley-express on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                berkeley-express
            
                    
    
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2. Uninstall "berkeley-express" package

In this section, we are going to explain the necessary steps to uninstall berkeley-express on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                berkeley-express
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the berkeley-express package on Ubuntu 20.10 (Groovy Gorilla)

Package: berkeley-express
Architecture: amd64
Version: 1.5.3+dfsg-1build3
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: 882
Depends: libbamtools2.5.1 (>= 2.5.1+dfsg), libboost-date-time1.71.0, libboost-filesystem1.71.0, libboost-program-options1.71.0, libboost-thread1.71.0, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libprotobuf23 (>= 3.12.3), libstdc++6 (>= 9)
Recommends: med-config (>= 2.1)
Filename: pool/universe/b/berkeley-express/berkeley-express_1.5.3+dfsg-1build3_amd64.deb
Size: 249320
MD5sum: fc2c8a31db90ff4942b244c37d99b421
SHA1: b9af95851c29d5d841e94558c64e88fe6f43ec08
SHA256: c5feaa83893c82f9dd9763071eb7a9b0bf65e360abb9ed57f06d89b8a41272b9
SHA512: 6cdcabbdfaf48c71191fcf96c42090b5f589ea85b20ff642c8fc0f16bcc5e9dfc42667f2e48471a6adf153659dcf3740d29edfd148d5854995a870c6a876d32b
Homepage: http://bio.math.berkeley.edu/eXpress/index.html
Description-en: Streaming quantification for high-throughput sequencing
eXpress is a streaming tool for quantifying the abundances of a set of
target sequences from sampled subsequences. Example applications include
transcript-level RNA-Seq quantification, allele-specific/haplotype
expression analysis (from RNA-Seq), transcription factor binding
quantification in ChIP-Seq, and analysis of metagenomic data. It is
based on an online-EM algorithm that results in space (memory)
requirements proportional to the total size of the target sequences and
time requirements that are proportional to the number of sampled
fragments. Thus, in applications such as RNA-Seq, eXpress can accurately
quantify much larger samples than other currently available tools
greatly reducing computing infrastructure requirements. eXpress can be
used to build lightweight high-throughput sequencing processing
pipelines when coupled with a streaming aligner (such as Bowtie), as
output can be piped directly into eXpress, effectively eliminating the
need to store read alignments in memory or on disk.
.
In an analysis of the performance of eXpress for RNA-Seq data, it was
observed that this efficiency does not come at a cost of accuracy.
eXpress is more accurate than other available tools, even when limited
to smaller datasets that do not require such efficiency. Moreover, like
the Cufflinks program, eXpress can be used to estimate transcript
abundances in multi-isoform genes. eXpress is also able to resolve
multi-mappings of reads across gene families, and does not require a
reference genome so that it can be used in conjunction with de novo
assemblers such as Trinity, Oases, or Trans-ABySS. The underlying model
is based on previously described probabilistic models developed for
RNA-Seq but is applicable to other settings where target sequences are
sampled, and includes parameters for fragment length distributions,
errors in reads, and sequence-specific fragment bias.
.
eXpress can be used to resolve ambiguous mappings in other
high-throughput sequencing based applications. The only required inputs
to eXpress are a set of target sequences and a set of sequenced
fragments multiply-aligned to them. While these target sequences will
often be gene isoforms, they need not be. Haplotypes can be used as the
reference for allele-specific expression analysis, binding regions for
ChIP-Seq, or target genomes in metagenomics experiments. eXpress is
useful in any analysis where reads multi-map to sequences that differ in
abundance.
Description-md5: 4d4c6aaf75f2e0fff660b1816f1f13c6