Package: NormalyzerDE
Title: Evaluation of normalization methods and calculation of differential expression analysis statistics
Version: 1.29.0
Author: Jakob Willforss
Authors@R: c(
    person("Jakob", "Willforss", email="jakob.willforss@hotmail.com", role=c("aut", "cre")),
    person("Aakash", "Chawade", role="aut"),
    person("Fredrik", "Levander", email="fredrik.levander@immun.lth.se", role=c("aut", "ths")))
Description: NormalyzerDE provides screening of normalization methods for 
    LC-MS based expression data. It calculates a range of normalized matrices 
    using both existing approaches and a novel time-segmented approach, 
    calculates performance measures and generates an evaluation report. 
    Furthermore, it provides an easy utility for Limma- or ANOVA- based 
    differential expression analysis.
Imports:
    vsn,
    preprocessCore,
    limma,
    MASS,
    ape,
    car,
    ggplot2,
    methods,
    utils,
    stats,
    SummarizedExperiment,
    matrixStats,
    ggforce
Suggests:
    knitr,
    testthat,
    rmarkdown,
    roxygen2,
    hexbin,
    BiocStyle
VignetteBuilder: knitr
biocViews:
    Normalization, MultipleComparison, Visualization, Bayesian, Proteomics, Metabolomics, DifferentialExpression
License: Artistic-2.0
Encoding: UTF-8
RoxygenNote: 7.2.3
URL: https://github.com/ComputationalProteomics/NormalyzerDE
Depends: R (>= 4.1.0)
git_url: https://git.bioconductor.org/packages/NormalyzerDE
git_branch: devel
git_last_commit: 1b37592
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
