prolfqua/DESCRIPTION at Modelling2R6 · fgcz/prolfqua · GitHub

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Package: prolfqua
Type: Package
Title: Proteomics Label Free Quantification
Version: 1.6.1
Authors@R: c(
    person("Witold", "Wolski",
        email = "witold.wolski@fgcz.uzh.ch",
        role = "aut",
        comment = c(ORCID = "0000-0002-6468-120X")),
    person("Functional Genomics Center Zurich",
        role = "fnd"),
    person("Christian", "Panse",
        email = "cp@fgcz.ethz.ch",
        role = "cre",
        comment = c(ORCID = "0000-0003-1975-3064")))
Description: The prolfqua package integrates essential steps
    of the mass spectrometry based label free quantification data
    analysis workflow: quality control, data normalization, protein aggregation,
    modeling, hypothesis testing and sample size estimation.
    We use prolfqua to : develop highly customizable, visually appealing,
    and interactive data analysis reports in pdf or HTML format;
    to visualize and model simple experimental designs
    with a single explanatory variable and complex experiments with multiple factors;
    to benchmark data acquisition,
    data preprocessing or data modeling methods.
    We developed and improved the package by applying the "Eating your own dog food" principle,
    when analysing dozens of proteomics datasets.
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
URL: https://github.com/fgcz/prolfqua,
    https://fgcz.github.io/prolfqua/
BugReports: https://github.com/fgcz/prolfqua/issues
Imports:
    dplyr,
    forcats,
    ggplot2,
    ggbeeswarm,
    ggrepel,
    limma,
    lme4,
    lmerTest,
    logistf,
    MASS,
    methods,
    pheatmap,
    plotly,
    progress,
    purrr,
    rlang,
    statmod,
    stringi,
    tidyselect,
    tidyr,
    tibble,
    UpSetR,
    withr
Suggests:
    BiocCheck,
    corrplot,
    covr,
    crosstalk,
    devtools,
    gridExtra,
    KernSmooth,
    knitr,
    limpa,
    lintr,
    pkgdown,
    preprocessCore,
    rcmdcheck,
    rmarkdown,
    roxygen2,
    S4Vectors,
    SummarizedExperiment,
    testthat,
    vsn,
    zCompositions
RoxygenNote: 7.3.3
Roxygen: list(r6 = TRUE)
Depends:
    R (>= 4.5.0)
biocViews: MassSpectrometry, Proteomics, Metabolomics, ExperimentHubSoftware, Normalization, Preprocessing, QualityControl