Package: omicsGMF
Type: Package
Authors@R: c(
        person("Alexandre", "Segers", role=c("aut", "cre", "fnd"), email="alexandresegers@outlook.com"),
        person("Cristian", "Castiglione", role=c("ctb"), email="cristian.castiglione@unipd.it"),
        person("Christophe", "Vanderaa", role = c("ctb"), email="christophe.vanderaa@ugent.be"),
        person("Davide", "Risso", role=c("ctb", "fnd"), email="davide.risso@unipd.it"),
        person("Lieven", "Clement", role=c("ctb", "fnd"), email="lieven.clement@ugent.be")
	)
Version: 1.0.0
Date: 2025-01-14
Title: Dimensionality reduction of (single-cell) omics data in R using
        omicsGMF
Description: omicsGMF is a Bioconductor package that uses the sgdGMF-framework of the \code{sgdGMF} package for highly performant 
    and fast matrix factorization that can be used for dimensionality reduction, visualization and imputation of omics
    data. It considers data from the general exponential family as input, and therefore suits the use of both RNA-seq
    (Poisson or Negative Binomial data) and proteomics data (Gaussian data). It does not require prior transformation of
    counts to the log-scale, because it rather optimizes the deviances from the data family specified. Also, it allows to 
    correct for known sample-level and feature-level covariates, therefore enabling visualization and dimensionality reduction
    upon batch correction. Last but not least, it deals with missing values, and allows to impute these after matrix 
    factorization, useful for proteomics data. This Bioconductor package allows input of SummarizedExperiment, 
    SingleCellExperiment, and QFeature classes.
biocViews: SingleCell, RNASeq, Proteomics, QualityControl,
        Preprocessing, Normalization, Visualization,
        DimensionReduction, Transcriptomics, GeneExpression,
        Sequencing, Software, DataRepresentation, MassSpectrometry
Depends: R (>= 4.5.0), sgdGMF, SingleCellExperiment, scuttle, scater
Imports: stats, utils, Matrix, S4Vectors, SummarizedExperiment,
        DelayedArray, MatrixGenerics, BiocSingular, BiocParallel,
        beachmat, ggplot2, methods, QFeatures
Suggests: knitr, dplyr, testthat, BiocGenerics, BiocStyle, graphics,
        grDevices
License: Artistic-2.0
URL: https://github.com/statOmics/omicsGMF
BugReports: https://github.com/statOmics/omicsGMF/issues
Config/testthat/edition: 3
VignetteBuilder: knitr
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Funding: This work was supported by grants from Ghent University
        Special Research Fund [BOF20/GOA/023] (A.S., L.C.), Research
        Foundation Flanders [FWO G062219N] (A.S., L.C.) and as WOG
        [W005325N] (L.C.). This work was supported by EU funding within
        the MUR PNRR ``National Center for HPC, big data and quantum
        computing'' (Project no. CN00000013 CN1). D.R. was also
        supported by the National Cancer Institute of the National
        Institutes of Health (U24CA289073). The views and opinions
        expressed are only those of the authors and do not necessarily
        reflect those of the European Union or the European Commission.
        Neither the European Union nor the European Commission can be
        held responsible for them.
git_url: https://git.bioconductor.org/packages/omicsGMF
git_branch: RELEASE_3_22
git_last_commit: 665af6c
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.22
Date/Publication: 2025-10-29
NeedsCompilation: no
Packaged: 2025-10-30 03:40:39 UTC; biocbuild
Author: Alexandre Segers [aut, cre, fnd],
  Cristian Castiglione [ctb],
  Christophe Vanderaa [ctb],
  Davide Risso [ctb, fnd],
  Lieven Clement [ctb, fnd]
Maintainer: Alexandre Segers <alexandresegers@outlook.com>
Built: R 4.5.1; ; 2025-10-30 09:34:24 UTC; unix
