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Provides an R interface for 'SSW' (Striped Smith-Waterman) via its 'Python' binding 'ssw-py'. 'SSW' is a fast 'C' and 'C++' implementation of the Smith-Waterman algorithm for pairwise sequence alignment using Single-Instruction-Multiple-Data (SIMD) instructions. 'SSW' enhances the standard algorithm by efficiently returning alignment information and suboptimal alignment scores. The core 'SSW' library offers performance improvements for various bioinformatics tasks, including protein database searches, short-read alignments, primary and split-read mapping, structural variant detection, and read-overlap graph generation. These features make 'SSW' particularly useful for genomic applications. Zhao et al. (2013) <doi:10.1371/journal.pone.0082138> developed the original 'C' and 'C++' implementation.
Version: | 0.2.1 |
Depends: | R (≥ 4.1.0) |
Imports: | reticulate |
Suggests: | knitr, rmarkdown |
Published: | 2024-09-18 |
DOI: | 10.32614/CRAN.package.ssw |
Author: | Nan Xiao [aut, cre, cph] |
Maintainer: | Nan Xiao <me at nanx.me> |
BugReports: | https://github.com/nanxstats/ssw-r/issues |
License: | MIT + file LICENSE |
URL: | https://nanx.me/ssw-r/, https://github.com/nanxstats/ssw-r |
NeedsCompilation: | no |
SystemRequirements: | Python (>= 3.6.0), ssw-py (>= 1.0.0). Detailed installation instructions can be found in the README file. |
Citation: | ssw citation info |
Materials: | README NEWS |
CRAN checks: | ssw results |
Reference manual: | ssw.pdf |
Vignettes: |
Getting started with ssw-r: Sequence alignment examples (source, R code) |
Package source: | ssw_0.2.1.tar.gz |
Windows binaries: | r-devel: ssw_0.2.1.zip, r-release: ssw_0.2.1.zip, r-oldrel: ssw_0.2.1.zip |
macOS binaries: | r-release (arm64): ssw_0.2.1.tgz, r-oldrel (arm64): ssw_0.2.1.tgz, r-release (x86_64): ssw_0.2.1.tgz, r-oldrel (x86_64): ssw_0.2.1.tgz |
Old sources: | ssw archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.