msa (version 1.4.3)

msa-package: Multiple Sequence Alignment

Description

The msa package provides a unified R/Bioconductor interface to different multiple sequence alignment algorithms. Currently, ‘ClustalW’, ‘ClustalOmega’, and ‘MUSCLE’ are supported. All algorithms are usable without additional software packages and on all major platforms. The multiple sequence algorithms are complemented by an R interface to the powerful LaTeX package texshade.sty which allows for a highly customizable plots of multiple sequence alignments.

Details

Package:

msa

Type:

Package

Version:

1.1.2

Date:

2015-09-29

License:

GPL-2

References

http://www.bioinf.jku.at/software/msa U. Bodenhofer, E. Bonatesta, C. Horejs-Kainrath, and S. Hochreiter (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: 10.1093/bioinformatics/btv494.

Thompson, J. D., Higgins, D. G., and Gibson, T. J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22(22):4673-4680. DOI: 10.1093/nar/22.22.4673.

Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Soeding, J., Thompson, J. D., and Higgins, D. G. (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7:539. DOI: 10.1038/msb.2011.75.

Edgar, R. C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32(5):1792-1797. DOI: 10.1093/nar/gkh340.

Edgar, R. C. (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113. DOI: 10.1186/1471-2105-5-113.

Beitz, E. (2000) TeXshade: shading and labeling of multiple sequence alignments using LaTeX2e Bioinformatics 16(2):135-139. DOI: 10.1093/bioinformatics/16.2.135.

See Also

msa, msaClustalW, msaClustalOmega, msaMuscle, msaPrettyPrint

Examples

## read sequences
filepath <- system.file("examples", "exampleAA.fasta", package="msa")
mySeqs <- readAAStringSet(filepath)

## call unified interface msa() for default method (ClustalW) and
## default parameters
msa(mySeqs)