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 externa
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Use bioconductor-msa to align the unaligned [DNA, RNA, or protein sequences] and return a consensus sequence and conservation summary; optionally produce a publication-ready alignment PDF.
Required inputs
[DNA, RNA, or protein sequences]
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SKILL.md
name: bioconductor-msadescription: 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 externawhen_to_use: "Use when: Performing multiple sequence alignment of amino acid or nucleotide sequences using msa().; Generating highly customizable, publication-ready PDF visualizations of alignments using msaPrettyPrint().; Calculating consensus sequences and conservation scores using msaConsensusSequence() and msaConservationScore().. Not for: For aligning massive genomic datasets (e.g., whole genomes), use minimap2 because msa is designed for gene- or protein-scale alignments.; For basic pairwise sequence alignments, use pwalign because it is specifically built for pairwise comparisons."user-invocable: false
msa
Dependencies & Environment
Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
Version: 1.44.0 · Bioconductor: 3.23 · R: ≥ 4.6
Depends: Biostrings
Imports: Rcpp, BiocGenerics, IRanges, S4Vectors
System requirements: GNU make
Install:BiocManager::install("msa")
When to Use
Performing multiple sequence alignment of amino acid or nucleotide sequences using msa().
Generating highly customizable, publication-ready PDF visualizations of alignments using msaPrettyPrint().
Calculating consensus sequences and conservation scores using msaConsensusSequence() and msaConservationScore().
When NOT to Use
For aligning massive genomic datasets (e.g., whole genomes), use minimap2 because msa is designed for gene- or protein-scale alignments.
For basic pairwise sequence alignments, use pwalign because it is specifically built for pairwise comparisons.
Data Requirements
Input Format: Unaligned DNA, RNA, or Amino Acid sequences.
Structure: Loaded as an AAStringSet (or similar XStringSet) using readAAStringSet().
Key Parameters
output ("pdf"): Format for pretty-printing (e.g., "pdf", "asis").
showNames ("none"): Controls the display of sequence names in the printed alignment.
showLogo ("none"): Controls the display of the sequence logo (e.g., "top", "none").
shadingMode ("similar"): Mode for color shading in the alignment (e.g., "similar", "functional").
type ("upperlower"): Type of consensus sequence to generate.
askForOverwrite (FALSE): Whether to prompt before overwriting existing files during PDF generation.
gapVsGap (0): Score assigned to gap-versus-gap matches when calculating conservation scores.
Best Practices
Use unmasked() to retrieve the original alignment if a colmask() has been applied to hide specific columns.
Convert alignments to other formats using msaConvert() for downstream phylogenetic analysis (e.g., with seqinr or ape).
Use output="asis" in msaPrettyPrint() when integrating alignments into Sweave or knitr documents.
Common Pitfalls
PDF Compilation Failures: msaPrettyPrint() failing to compile PDFs; fix this by ensuring a working LaTeX system with the texshade.sty package is installed on your system path.
Alignments Running Off Page: Large alignments running off the page in PDFs; fix this by splitting the alignment into chunks using subseq() and printing them separately.
Memory Exhaustion: Running ClustalW on thousands of sequences can consume excessive memory; fix this by switching to ClustalOmega for large datasets.
Alternatives
DECIPHER: A powerful Bioconductor package for sequence alignment, database management, and oligonucleotide design.
ape: For phylogenetic analysis and basic sequence manipulation.
seqinr: For biological sequence retrieval and analysis.
Citations
Bodenhofer U, Bonatesta E, Horejs-Kainrath C, Hochreiter S. (2015) "msa: an R package for multiple sequence alignment." Bioinformatics.
This skill is the knowledge layer — when, why, and how to use msa. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.