| name | bioconductor-biostrings |
| description | Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences. |
| when_to_use | Use when: Representing and manipulating biological sequences using specialized classes like BString, DNAString, and RNAString.; Matching sets of probes against each other using PDict and vcountPDict.; Computing base content (e.g., GC content) of sequences using alphabetFrequency.; Handling and masking multiple sequence alignments (DNA, RNA, or amino acids) using DNAMultipleAlignment and rowmask/colmask.; Ca. Not for: For standard character string manipulation not involving biological sequences; use base R character vectors or stringr instead because they have less overhead.; For ultra-fast, genome-scale alignment of millions of short sequencing reads; use externa |
| user-invocable | false |
Biostrings
Dependencies & Environment
Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
- Version: 2.80.1 · Bioconductor: 3.23 · R: ≥ 4.6
- Depends: BiocGenerics, S4Vectors, IRanges, XVector, Seqinfo
- Imports: crayon
- Install:
BiocManager::install("Biostrings")
When to Use
- Representing and manipulating biological sequences using specialized classes like
BString, DNAString, and RNAString.
- Matching sets of probes against each other using
PDict and vcountPDict.
- Computing base content (e.g., GC content) of sequences using
alphabetFrequency.
- Handling and masking multiple sequence alignments (DNA, RNA, or amino acids) using
DNAMultipleAlignment and rowmask/colmask.
- Calculating consensus matrices and strings from masked alignments using
consensusMatrix and consensusString.
When NOT to Use
- For standard character string manipulation not involving biological sequences; use base R
character vectors or stringr instead because they have less overhead.
- For ultra-fast, genome-scale alignment of millions of short sequencing reads; use external command-line aligners (e.g., Minimap2, Bowtie2) instead.
Data Requirements
- Input sequences in FASTA, Clustal, Phylip, or Stolkholm formats for multiple alignments.
- Character vectors or probe sequence data packages (e.g.,
hgu95av2probe) for sequence manipulation.
Key Parameters
- baseOnly: Logical to compute frequencies of only the standard bases in
alphabetFrequency.
- collapse: Logical to sum frequencies across all sequences in
alphabetFrequency.
- filepath: Path to the alignment file in
readDNAMultipleAlignment.
- format: Format of the alignment file (e.g., "clustal", "phylip").
- invert: Logical to specify rows/columns to keep rather than hide when setting masks.
- append: Specifies how new mask ranges interact with existing masks ("union", "intersect", "replace").
- min.fraction: Fraction of gaps required to mask a column in
maskGaps.
- min.block.width: Minimum width of gap blocks to mask in
maskGaps.
Best Practices
- Use
DNAStringSet instead of lists of DNAString objects to leverage vectorized operations.
- Apply
rowmask and colmask to MultipleAlignment objects to non-destructively hide uninformative regions or gaps before clustering.
- Use
maskGaps to automatically mask columns based on gap fractions.
- Cast
MultipleAlignment objects to DNAStringSet before exporting to FASTA with writeXStringSet.
Common Pitfalls
- Incompatible sequence alphabets: Attempting to compare a
DNAString with an RNAString directly. Fix: Convert sequences using RNAString(d) before comparison.
- Clustering unmasked alignments: Generating phylogenetic trees with long uninformative regions, leading to inflated distances. Fix: Use
maskGaps to remove gap-heavy columns before calculating stringDist.
- Losing masks on export: Exporting to formats that don't support masks. Fix: Use
write.phylip to preserve column masking, or cast to matrix to drop masked regions entirely.
Alternatives
- seqinr: For biological sequence retrieval and analysis, but uses standard R lists/characters which are less memory-efficient.
- ape: For phylogenetics and sequence manipulation, but lacks the specialized S4 infrastructure and non-destructive masking of Biostrings.
- DECIPHER: For large-scale sequence alignment, database management, and oligonucleotide design, built on top of Biostrings.
Citations
- Pagès, H. et al. (2024). Biostrings: Efficient manipulation of biological strings. R package version 2.74.1.
References
Run this on BioMate
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