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Bioconductor 3.22 Released

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msa

This is thereleased version of msa; for the devel version, seemsa.

Multiple Sequence Alignment

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DOI: 10.18129/B9.bioc.msa


Bioconductor version: Release (3.22)

The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.

Author: Enrico Bonatesta [aut], Christoph Kainrath [aut], Ulrich Bodenhofer [aut, cre, ths]

Maintainer: Ulrich Bodenhofer <ulrich at bodenhofer.com>

Citation (from within R, entercitation("msa")):

Installation

To install this package, start R (version "4.5") and enter:

if (!require("BiocManager", quietly = TRUE))    install.packages("BiocManager")BiocManager::install("msa")

For older versions of R, please refer to the appropriateBioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("msa")
msa - An R Package for Multiple Sequence AlignmentPDFR Script
Reference ManualPDF
NEWSText

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsAlignment,MultipleComparison,MultipleSequenceAlignment,Sequencing,Software
Version1.42.0
In Bioconductor sinceBioC 3.1 (R-3.2) (10.5 years)
LicenseGPL (>= 2)
DependsR (>= 3.3.0), methods,Biostrings(>= 2.40.0)
ImportsRcpp (>= 0.11.1),BiocGenerics,IRanges(>= 1.20.0),S4Vectors, tools
System RequirementsGNU make
URLhttps://github.com/UBod/msa
See More
SuggestsBiobase,knitr,seqinr,ape (>= 5.1),phangorn,pwalign
Linking ToRcpp
Enhances
Depends On Me
Imports MeDspikeIn,LymphoSeq,odseq,rhinotypeR,surfaltr
Suggests Meidpr,AntibodyForests,bio3d,BOLDconnectR,SVAlignR
Links To Me
Build ReportBuild Report

Package Archives

FollowInstallation instructions to use this package in your R session.

Source Packagemsa_1.42.0.tar.gz
Windows Binary (x86_64) msa_1.42.0.zip (64-bit only)
macOS Binary (x86_64)msa_1.42.0.tgz
macOS Binary (arm64)msa_1.42.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/msa
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/msa
Bioc Package Browserhttps://code.bioconductor.org/browse/msa/
Package Short Urlhttps://bioconductor.org/packages/msa/
Package Downloads ReportDownload Stats

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