How to Install and Uninstall r-cran-tigger Package on Kali Linux

Last updated: November 23,2024

1. Install "r-cran-tigger" package

This is a short guide on how to install r-cran-tigger on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-tigger
            
                    
    
    Copied

2. Uninstall "r-cran-tigger" package

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


    
        
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                sudo apt remove
            
                        
                r-cran-tigger
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-cran-tigger package on Kali Linux

Package: r-cran-tigger
Version: 1.1.0-1
Installed-Size: 4159
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-api-4.0, r-cran-ggplot2 (>= 3.4.0), r-cran-alakazam (>= 1.3.0), r-cran-dplyr (>= 1.0.0), r-cran-doparallel, r-cran-foreach, r-cran-gridextra, r-cran-gtools, r-cran-iterators, r-cran-lazyeval, r-cran-rlang, r-cran-stringi, r-cran-tidyr (>= 1.1.0)
Suggests: r-cran-knitr, r-cran-rmarkdown, r-cran-testthat
Size: 4099664
SHA256: f385ae3cd223c64c33a423d228a60b3235fbe48ec1801cece65770a54dc95997
SHA1: 5dec99a24cef2da76bf1d1395e504786033862fd
MD5sum: 8644f62b384e6e4e8f9598cd702c6eb0
Description: Infers new Immunoglobulin alleles from Rep-Seq Data
Summary: Infers the V genotype of an individual from immunoglobulin (Ig)
repertoire-sequencing (Rep-Seq) data, including detection of any novel
alleles. This information is then used to correct existing V allele calls
from among the sample sequences.
.
High-throughput sequencing of B cell immunoglobulin receptors is
providing unprecedented insight into adaptive immunity. A key step in
analyzing these data involves assignment of the germline V, D and J gene
segment alleles that comprise each immunoglobulin sequence by matching
them against a database of known V(D)J alleles. However, this process
will fail for sequences that utilize previously undetected alleles,
whose frequency in the population is unclear.
.
TIgGER is a computational method that significantly improves V(D)J
allele assignments by first determining the complete set of gene segments
carried by an individual (including novel alleles) from V(D)J-rearrange
sequences. TIgGER can then infer a subject’s genotype from these
sequences, and use this genotype to correct the initial V(D)J allele
assignments.
.
The application of TIgGER continues to identify a surprisingly high
frequency of novel alleles in humans, highlighting the critical need
for this approach. TIgGER, however, can and has been used with data
from other species.
.
Core Abilities:
* Detecting novel alleles
* Inferring a subject’s genotype
* Correcting preliminary allele calls
.
Required Input
* A table of sequences from a single individual, with columns containing
the following:
- V(D)J-rearranged nucleotide sequence (in IMGT-gapped format)
- Preliminary V allele calls
- Preliminary J allele calls
- Length of the junction region
* Germline Ig sequences in IMGT-gapped fasta format (e.g., as those
downloaded from IMGT/GENE-DB)
.
The former can be created through the use of IMGT/HighV-QUEST and
Change-O.
Description-md5:
Homepage: https://cran.r-project.org/package=tigger
Section: science
Priority: optional
Filename: pool/main/r/r-cran-tigger/r-cran-tigger_1.1.0-1_all.deb