DESCRIPTION

Package: prolfqua
Type: Package
Title: Proteomics Label Free Quantification
Version: 1.3.6
Authors@R: c(person("Witold", "Wolski",
        email = "wew@fgcz.ethz.ch",
        role = c("aut", "cre"),
        comment = c(ORCID = "0000-0002-6468-120X")))
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, making it easy to use.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/wolski/prolfqua
BugReports: https://github.com/wolski/prolfqua/issues
Imports:
    bookdown,
    broom,
    conflicted,
    data.table,
    dplyr,
    dtplyr,
    DT,
    forcats,
    gridExtra,
    ggplot2,
    ggbeeswarm,
    ggrepel,
    ggridges,
    ggpubr,
    htmlwidgets,
    lme4,
    lmerTest,
    MASS,
    multcomp,
    pheatmap,
    plotly,
    progress,
    purrr,
    readr,
    readxl,
    rlang,
    statmod,
    stringr,
    tidyr,
    tibble,
    UpSetR,
    yaml,
    writexl
Suggests:
    corrplot,
    docopt,
    knitr,
    rmarkdown,
    S4Vectors,
    testthat,
    SummarizedExperiment,
    proDA,
    vsn
RoxygenNote: 7.3.2
Roxygen: list(r6 = TRUE)
Depends: 
    R (>= 4.1)
biocViews: MassSpectrometry, Proteomics, Metabolomics, ExperimentHubSoftware, Normalization, Preprocessing, QualityControl