Package: mums2
Title: Microbial Ecology by Tandem Mass Spectrometry
Version: 0.1.1.9000
Authors@R: c(
    person("Allison", "Mason", , "masonar@umich.edu", role = c("aut"),
            comment = c(ORCID = "0000-0003-1339-1592")),
    person("Gregory", "Johnson", , "grejoh@umich.edu", role = c("aut"),
            comment = c(ORCID = "0009-0008-3890-0297")),
    person("Patrick", "Schloss", , "pschloss@umich.edu", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-6935-4275")),
    person("Anton", "Pervukhin", , "apervukh@minet.uni-jena.de", role = c("ctb", "cph")),
    person("Florian", "Rasche", , "m3rafl@minet.uni-jena.de", role = c("ctb", "cph")),
    person("Henner", "Sudek", , "Henner.Sudek@CeBiTec.Uni-Bielefeld.DE", role = c("ctb", "cph")),
    person("Marcel", "Martin", , "Marcel.Martin@CeBiTec.Uni-Bielefeld.DE", role = c("ctb", "cph")),
    person("Yuanyue", "Li", , "mail@yli.one", role = c("ctb", "cph"))
            )
Description: Tools that researchers can use to analyze untargeted
        metabolomics data generated using tandem mass spectroscopy from
        microbial communities. The overall approach taken to analyze
        metabolomics data parallels that used to analyze microbial
        communities using 16S rRNA gene sequencing data. Thus, we have
        a number of methods a user is able to use to generate data.
        Firstly, users can import Mass Spectrometry 1(MS1) data and
        filter it. Users are then able to match Mass Spectrometry
        2(MS2) data to the filtered (or unfiltered) MS1 data. With the
        matched data users are able to cluster it, annotate it, predict
        de novo chemical formulas and calculate alpha and beta
        diversity. For chemical formula predictions, this was the
        method used; "Towards de novo identification of metabolites by
        analyzing tandem mass spectra" (Sebastian Böcker, Florian
        Rasche (2008) <doi:10.1093/bioinformatics/btn270>). The
        similarity/dissimilarity calculations we used to cluster our
        data together was: "Spectral entropy outperforms MS/MS dot
        product similarity for small-molecule compound identification"
        (Li, Y., Kind, T., Folz, J. et al. (2021)
        <doi:10.1038/s41592-021-01331-z>) and "Sharing and community
        curation of mass spectrometry data with Global Natural Products
        Social Molecular Networking" (Wang, M., Carver, J., Phelan, V.
        et al. (2021) <doi:10.1038/nbt.3597>).
License: GPL (>= 3)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
URL: https://github.com/mums2/mums2, https://www.mums2.org/mums2/
BugReports: https://github.com/mums2/mums2/issues
LinkingTo: sitmo, Rcpp, RcppThread, testthat, RcppProgress
Imports: clustur, Rcpp, data.table, mpactr, utils, stats, parallel,
        xml2, RaMS
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tidyverse, networkD3
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/Needs/website: rmarkdown
Config/roxygen2/version: 8.0.0
RoxygenNote: 7.3.2
Config/pak/sysreqs: cmake libfontconfig1-dev libfreetype6-dev
        libfribidi-dev make libharfbuzz-dev libicu-dev libjpeg-dev
        libpng-dev libuv1-dev libxml2-dev libssl-dev
Repository: https://mums2.r-universe.dev
Date/Publication: 2026-06-25 13:36:25 UTC
RemoteUrl: https://github.com/mums2/mums2
RemoteRef: HEAD
RemoteSha: a8f58bc5b5e732d4dc7541d919bdc4f16b498896
NeedsCompilation: yes
Packaged: 2026-06-25 14:26:03 UTC; root
Author: Allison Mason [aut] (ORCID: <https://orcid.org/0000-0003-1339-1592>),
  Gregory Johnson [aut] (ORCID: <https://orcid.org/0009-0008-3890-0297>),
  Patrick Schloss [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-6935-4275>),
  Anton Pervukhin [ctb, cph],
  Florian Rasche [ctb, cph],
  Henner Sudek [ctb, cph],
  Marcel Martin [ctb, cph],
  Yuanyue Li [ctb, cph]
Maintainer: Patrick Schloss <pschloss@umich.edu>
Depends: R (>= 4.1.0)