{ "_id": "6a32688d3efcd9bda43864d3", "Package": "easyLSEA", "Title": "Lipid Set Enrichment Analysis with Dual KS and 'fgsea' Engines", "Version": "0.2.1", "Authors@R": "person(\"David\", \"Guardamino Ojeda\",\nrole = c(\"aut\", \"cre\"),\nemail = \"david.guardamino@gmail.com\",\ncomment = c(ORCID = \"0000-0002-3122-2218\"))", "Description": "Provides biology-aware lipid set enrichment analysis\n(LSEA) for lipidomics data using dual engines: the\nKolmogorov-Smirnov test and the fast gene set enrichment\nalgorithm from the 'fgsea' package. Annotates lipids into\nbiological groups at three levels (lipid class, LIPID MAPS\ncategory, functional category) and tests for coordinated\ndirectional shifts between conditions. Includes fatty acid\nchain analysis with trend plots weighted by lipid abundance\n(Spearman rank correlation, configurable smoothing),\nwide-format chain position output (sn-1, sn-2, sn-3, sn-4),\nannotation confidence filtering, and export utilities for\nreproducible reporting in CSV, 'Excel', and PDF formats.\nVignettes are available in English and Spanish. Methods are\nbased on Subramanian et al. (2005)\n and Korotkevich et al. (2021)\n.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "8.0.0", "URL": "https://github.com/DavidGO464/easyLSEA", "BugReports": "https://github.com/DavidGO464/easyLSEA/issues", "LazyData": "true", "Config/testthat/edition": "3", "VignetteBuilder": "knitr", "Language": "en-US", "Repository": "https://davidgo464.r-universe.dev", "Date/Publication": "2026-06-08 17:43:09 UTC", "RemoteUrl": "https://github.com/davidgo464/easylsea", "RemoteRef": "HEAD", "RemoteSha": "27773178bbf2abbe1e656e879d559856c87d580f", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-17 09:23:48 UTC", "User": "root" }, "Author": "David Guardamino Ojeda [aut, cre] (ORCID:\n)", "Maintainer": "David Guardamino Ojeda ", "MD5sum": "c0e578707c6126d61f790aa15eafe834", "_user": "davidgo464", "_type": "src", "_file": "easyLSEA_0.2.1.tar.gz", "_fileid": "b0361572233479a1f128840a5ff0b7132c1f522bdedcb0d0ac894d0db09db328", "_filesize": 519704, "_sha256": 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