Source: r-bioc-mofa2
Standards-Version: 4.7.4
Maintainer: Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
Uploaders:
 Steffen Moeller <moeller@debian.org>,
Section: gnu-r
Testsuite: autopkgtest-pkg-r
Build-Depends:
 debhelper-compat (= 14),
 dh-r,
 r-base-dev,
 r-bioc-rhdf5,
 r-cran-dplyr,
 r-cran-tidyr,
 r-cran-reshape2,
 r-cran-pheatmap,
 r-cran-ggplot2,
 r-cran-rcolorbrewer,
 r-cran-cowplot,
 r-cran-ggrepel,
 r-cran-reticulate,
 r-bioc-hdf5array,
 r-cran-magrittr,
 r-cran-forcats,
 r-cran-corrplot,
 r-bioc-delayedarray,
 r-cran-rtsne,
 r-cran-uwot,
 r-cran-stringi,
 r-pkg-team-core-architecture,
Vcs-Browser: https://salsa.debian.org/r-pkg-team/r-bioc-mofa2
Vcs-Git: https://salsa.debian.org/r-pkg-team/r-bioc-mofa2.git
Homepage: https://bioconductor.org/packages/MOFA2/

Package: r-bioc-mofa2
Architecture: all
Depends:
 ${R:Depends},
 ${shlibs:Depends},
 ${misc:Depends},
 r-pkg-team-core-architecture,
 python3,
Recommends:
 ${R:Recommends},
Suggests:
 ${R:Suggests},
Description: Multi-Omics Factor Analysis v2
 The MOFA2 package contains a collection of tools for training and analysing
 multi-omic factor analysis (MOFA). MOFA is a probabilistic factor model that
 aims to identify principal axes of variation from data sets that can comprise
 multiple omic layers and/or groups of samples. Additional time or space
 information on the samples can be incorporated using the MEFISTO framework,
 which is part of MOFA2. Downstream analysis functions to inspect molecular
 features underlying each factor, visualisation, imputation etc are available.
