{ "_id": "6a1f0134b401979e7341af9e", "Package": "ssw", "Title": "Striped Smith-Waterman Algorithm for Sequence Alignment using\nSIMD", "Version": "0.2.1", "Authors@R": "c(\nperson(\"Nan\", \"Xiao\", email = \"me@nanx.me\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-0250-5673\"))\n)", "Description": "Provides an R interface for 'SSW' (Striped Smith-Waterman)\nvia its 'Python' binding 'ssw-py'. 'SSW' is a fast 'C' and\n'C++' implementation of the Smith-Waterman algorithm for\npairwise sequence alignment using\nSingle-Instruction-Multiple-Data (SIMD) instructions. 'SSW'\nenhances the standard algorithm by efficiently returning\nalignment information and suboptimal alignment scores. The core\n'SSW' library offers performance improvements for various\nbioinformatics tasks, including protein database searches,\nshort-read alignments, primary and split-read mapping,\nstructural variant detection, and read-overlap graph\ngeneration. These features make 'SSW' particularly useful for\ngenomic applications. Zhao et al. (2013)\n developed the original 'C'\nand 'C++' implementation.", "License": "MIT + file LICENSE", "URL": "https://nanx.me/ssw-r/, https://github.com/nanxstats/ssw-r", "BugReports": "https://github.com/nanxstats/ssw-r/issues", "Encoding": "UTF-8", "SystemRequirements": "Python (>= 3.6.0), ssw-py (>= 1.0.0). Detailed\ninstallation instructions can be found in the README file.", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "Config/pak/sysreqs": "libpng-dev python3", "Repository": "https://nanxstats.r-universe.dev", "Date/Publication": "2024-09-17 22:19:48 UTC", "RemoteUrl": "https://github.com/nanxstats/ssw-r", "RemoteRef": "HEAD", "RemoteSha": "9b36eb0fcb17d5027d3aaf33d2f680200414eeb7", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-18 08:45:54 UTC", "User": "root" }, "Author": "Nan Xiao [aut, cre, cph] (ORCID:\n)", "Maintainer": "Nan Xiao ", "MD5sum": "72679ea04b8ef143a17d85b44f848b5e", "_user": "nanxstats", "_type": "src", "_file": "ssw_0.2.1.tar.gz", "_fileid": "31e172da3c4dc0614e4869e48676989b3df4d8d8819fa8b74d131e34ad253e1d", "_filesize": 149098, "_sha256": "31e172da3c4dc0614e4869e48676989b3df4d8d8819fa8b74d131e34ad253e1d", "_created": "2026-05-18T08:45:54.000Z", "_published": "2026-06-02T16:13:40.983Z", "_distro": "noble", "_jobs": 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