Package: MatrixQCvis
Type: Package
Title: Shiny-based interactive data-quality exploration for omics data
Version: 1.20.2
Date: 2026-08-17
Authors@R: c(person("Thomas", "Naake", role = c("aut", "cre"), 
		email = "thomasnaake@googlemail.com",
		comment = c(ORCID = "0000-0001-7917-5580")),
    person("Wolfgang", "Huber", role = c("aut"), 
		email = "wolfgang.huber@embl.de",
		comment = c(ORCID = "0000-0002-0474-2218")))
VignetteBuilder: knitr
Description: Data quality assessment is an integral part of preparatory
        data analysis to ensure sound biological information retrieval.
        We present here the MatrixQCvis package, which provides
        shiny-based interactive visualization of data quality metrics
        at the per-sample and per-feature level. It is broadly
        applicable to quantitative omics data types that come in
        matrix-like format (features x samples). It enables the
        detection of low-quality samples, drifts, outliers and batch
        effects in data sets. Visualizations include amongst others
        bar- and violin plots of the (count/intensity) values, mean vs
        standard deviation plots, MA plots, empirical cumulative
        distribution function (ECDF) plots, visualizations of the
        distances between samples, and multiple types of dimension
        reduction plots. Furthermore, MatrixQCvis allows for
        differential expression analysis based on the limma (moderated
        t-tests) and proDA (Wald tests) packages. MatrixQCvis builds
        upon the popular Bioconductor SummarizedExperiment S4 class and
        enables thus the facile integration into existing workflows.
        The package is especially tailored towards metabolomics and
        proteomics mass spectrometry data, but also allows to assess
        the data quality of other data types that can be represented in
        a SummarizedExperiment object.
Depends: R (>= 4.1.0), DT (>= 0.33), SummarizedExperiment (>= 1.20.0),
        plotly (>= 4.9.3), shiny (>= 1.6.0)
Imports: ComplexHeatmap (>= 2.7.9), dplyr (>= 1.0.5), ExperimentHub (>=
        2.6.0), ggplot2 (>= 3.3.3), grDevices (>= 4.1.0), Hmisc (>=
        4.5-0), htmlwidgets (>= 1.5.3), impute (>= 1.65.0), imputeLCMD
        (>= 2.0), limma (>= 3.47.12), MASS (>= 7.3-58.1), methods (>=
        4.1.0), pcaMethods (>= 1.83.0), proDA (>= 1.5.0), rlang (>=
        0.4.10), rmarkdown (>= 2.7), Rtsne (>= 0.15), shinydashboard
        (>= 0.7.1), shinyhelper (>= 0.3.2), shinyjs (>= 2.0.0), stats
        (>= 4.1.0), sva (>= 3.52.0), tibble (>= 3.1.1), tidyr (>=
        1.1.3), umap (>= 0.2.7.0), UpSetR (>= 1.4.0), vsn (>= 3.59.1)
Suggests: BiocGenerics (>= 0.37.4), BiocStyle (>= 2.19.2), hexbin (>=
        1.28.2), httr (>= 1.4.7), jpeg (>= 0.1-10), knitr (>= 1.33),
        statmod (>= 1.5.0), testthat (>= 3.0.2)
biocViews: Visualization, ShinyApps, GUI, QualityControl,
        DimensionReduction, Metabolomics, Proteomics, Transcriptomics
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.1
Config/pak/sysreqs: cmake make libicu-dev libpng-dev libuv1-dev
        libxml2-dev libssl-dev perl python3 zlib1g-dev
Repository: Bioconductor 3.23
Date/Publication: 2026-08-17 13:37:18 UTC
RemoteUrl: https://github.com/bioc/MatrixQCvis
RemoteRef: RELEASE_3_23
RemoteSha: c915e167bad19ba0f4f9bfed9687564f7af39e4c
NeedsCompilation: no
Packaged: 2026-08-17 20:10:03 UTC; root
Author: Thomas Naake [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-7917-5580>),
  Wolfgang Huber [aut] (ORCID: <https://orcid.org/0000-0002-0474-2218>)
Maintainer: Thomas Naake <thomasnaake@googlemail.com>
Built: R 4.6.1; ; 2026-08-17 20:12:42 UTC; unix
