Package: TaxSEA
Type: Package
Title: Taxon Set Enrichment Analysis
Version: 1.5.7
Authors@R: c(person("Feargal", "Ryan", 
    email = "feargalr@gmail.com", 
    role = c("aut", "cre","fnd"),comment = c(ORCID = "0000-0002-1565-4598",
                      funding = "Supported by NHMRC Investigator Grant")))
Description: TaxSEA makes metagenomic data easier to interpret. Rather than
    reading species one at a time, it tests whether a-priori defined sets of
    taxa shift together, drawing on public databases (BugSigDB, MiMeDB,
    GutMGene, mBodyMap, BacDive and GMRepoV2) and on sets collated from the
    literature. Two approaches are provided. TaxSEA takes taxon names or NCBI
    IDs with a rank per taxon, such as a fold change or correlation
    coefficient, and tests each set with a Kolmogorov-Smirnov test. ssTaxSEA
    scores every set in a single sample as the mean centered log-ratio of its
    members, giving a per-sample value to use in any downstream model. Both
    work with any taxonomic profiling technology, including 16S rRNA gene
    sequencing, shotgun metagenomics and metatranscriptomics.
License: GPL-3
Encoding: UTF-8
LazyData: false
VignetteBuilder: knitr
biocViews: Microbiome, Metagenomics, Sequencing, GeneSetEnrichment,
        RNASeq
URL: https://github.com/feargalr/taxsea,
        https://feargalr.github.io/TaxSEA/
BugReports: https://github.com/feargalr/taxsea/issues
Depends: R (>= 4.6.0)
Suggests: BiocStyle, S4Vectors, bugsigdbr, fgsea, knitr, mia,
        rmarkdown, SummarizedExperiment, testthat
Imports: methods, stats, utils
Config/testthat/edition: 3
Config/roxygen2/version: 8.1.0
git_url: https://git.bioconductor.org/packages/TaxSEA
git_branch: devel
git_last_commit: 0fde543
git_last_commit_date: 2026-09-20
Repository: Bioconductor 3.24
Date/Publication: 2026-09-21
NeedsCompilation: no
Packaged: 2026-09-22 00:33:23 UTC; biocbuild
Author: Feargal Ryan [aut, cre, fnd] (ORCID:
    <https://orcid.org/0000-0002-1565-4598>, funding: Supported by
    NHMRC Investigator Grant)
Maintainer: Feargal Ryan <feargalr@gmail.com>
