# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "omicsGMF" in publications use:'
type: software
license: Artistic-2.0
title: 'omicsGMF: Dimensionality reduction of (single-cell) omics data in R using
  omicsGMF'
version: 1.2.0
doi: 10.32614/CRAN.package.omicsGMF
abstract: omicsGMF is a Bioconductor package that uses the sgdGMF-framework of the
  \codesgdGMF 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.
authors:
- family-names: Segers
  given-names: Alexandre
  email: alexandresegers@outlook.com
repository: https://bioc-release.r-universe.dev
repository-code: https://github.com/statOmics/omicsGMF
commit: 882ea718f968c2c963154c06ff4b4a368d1e6cfa
url: https://github.com/statOmics/omicsGMF
date-released: '2025-01-14'
contact:
- family-names: Segers
  given-names: Alexandre
  email: alexandresegers@outlook.com