Package: prolfqua
Type: Package
Title: Proteomics Label Free Quantification
Version: 0.99.8
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: prolfqua covers the steps of a mass spectrometry based
    label-free quantification (LFQ) analysis: quality control, normalization,
    aggregation of peptides to proteins, modelling, hypothesis testing and
    sample size estimation. A single function, build_contrast_analysis(), fits a
    model per protein and computes contrasts with one of many methods: linear,
    robust and rank-based regression, limma and limma-voom, DEqMS variance
    moderation, limpa's detection probability model, Firth logistic and binomial
    models of detection, mixed models and ROPECA on peptide-level data, a hurdle
    model combining intensity and detection, and variants that impute groups
    without observations at the limit of detection. All methods return their
    results through the same interface and columns, so they can be compared and
    combined. prolfqua models simple designs with one explanatory variable as
    well as experiments with several factors, and was developed while analysing
    dozens of proteomics datasets at the Functional Genomics Center Zurich.
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: circlize, ComplexHeatmap, dplyr, forcats, ggplot2, ggbeeswarm,
        ggrepel, limma, lme4, lmerTest, logistf, MASS, methods, plotly,
        progress, purrr, rlang, stringi, tidyselect, tidyr, tibble,
        UpSetR, withr
Suggests: BiocCheck, BiocStyle, corrplot, covr, crosstalk, cyclocomp,
        devtools, goodpractice, gridExtra, KernSmooth, knitr, limpa,
        lintr, pkgdown, preprocessCore, rcmdcheck, Rfit, rmarkdown,
        roxygen2, S4Vectors, SummarizedExperiment, testthat, vsn
Roxygen: list(r6 = TRUE)
Depends: R (>= 4.6)
biocViews: MassSpectrometry, Proteomics, Metabolomics, Normalization,
        Preprocessing, QualityControl
Config/roxygen2/version: 8.1.1
git_url: https://git.bioconductor.org/packages/prolfqua
git_branch: devel
git_last_commit: 268ef2c4
git_last_commit_date: 2026-11-03
Repository: Bioconductor 3.24
Date/Publication: 2026-11-04
NeedsCompilation: no
Packaged: 2026-11-05 00:48:22 UTC; biocbuild
Author: Witold Wolski [aut] (ORCID: <https://orcid.org/0000-0002-6468-120X>),
  Functional Genomics Center Zurich [fnd],
  Christian Panse [cre] (ORCID: <https://orcid.org/0000-0003-1975-3064>)
Maintainer: Christian Panse <cp@fgcz.ethz.ch>
