Package: EMTscore
Type: Package
Title: Calculate EMT Scores Based on Omics Data
Version: 0.99.10
Date: 2026-08-04
Authors@R: c(
    person(given = "Haimei", family = "Wen",
           email = "hudie.luoluo@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0009-0006-1600-1210")),
    person(given = "Daniel", family = "Lopez", role = "aut"),
    person(given = "Tian", family = "Hong", role = "aut"),
    person("National Institutes of Health", role = "fnd",
           comment = c(grant = "R35GM149531")),
    person("National Science Foundation", role = "fnd",
           comment = c(grant = "2243562")))
Description: Epithelial-mesenchymal transition (EMT) is an important
        form of cellular plasticity that is fully or partially
        activated in several biological scenarios including development
        and disease progression. EMT involves altered expression of
        hundreds of protein-coding and non-protein-coding genes. Recent
        studies showed the prevalence of partial EMT in multiple
        processes such as various cancers and organ fibrosis, which
        necessitates rigorous quantification of the degree of EMT.
        While traditional gene set scoring methods such as gene set
        variation analysis have been used to generate EMT scores from
        omics data, multiple EMT scoring algorithms and EMT gene sets
        have been used by different groups without standardization.
        Furthermore, comparisons of EMT scores computed from different
        methods and/or different EMT gene sets are generally difficult
        due to both the context dependent nature of EMT and the lack of
        tools that comprehensively integrate varying components for EMT
        scoring. To address this problem, EMTscore enables users to
        select scoring methods from a list of previously used
        algorithms and EMT gene sets from a list of gene sets produced
        from different experiments. Several visualization methods are
        provided for making publication-quality plots of EMT scores
        from omics data. The package also implements a
        principal-component-analysis based method for scoring divergent
        EMT processes from a single dataset. Overall, EMTscore provides
        an integrated solution for assessing the degree and complexity
        of EMT from omics data, and paves the way for standardizing the
        comparison of EMT programs across multiple contexts.
License: GPL-3
URL: https://github.com/wenmm/EMTscore
BugReports: https://github.com/wenmm/EMTscore/issues
Encoding: UTF-8
biocViews: Software, GeneExpression, GeneSetEnrichment, SingleCell,
        Transcriptomics, Visualization, RNASeq, DimensionReduction,
        PrincipalComponent, MultipleComparison
Imports: AUCell, BiocParallel, circlize, ComplexHeatmap, dplyr, GSA,
        GSEABase, ggplot2, ggpubr, GSVA, magrittr, Matrix, mclust,
        nsprcomp, rlang, Seurat, stats, utils
Suggests: testthat, knitr, rmarkdown, BiocStyle, BiocFileCache,
        EMTscoreData, ExperimentHub, SingleCellExperiment,
        SummarizedExperiment, Cairo, RColorBrewer, curl, ggalluvial,
        ggtext, ggthemes, gridExtra, paletteer, pheatmap
VignetteBuilder: knitr
RoxygenNote: 7.3.3
LazyData: false
NeedsCompilation: no
Depends: R (>= 4.5.0)
Config/pak/sysreqs: cmake libglpk-dev make libmagick++-dev gsfonts
        libicu-dev libpng-dev libuv1-dev libxml2-dev libssl-dev perl
        python3 zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-08-04 21:30:00 UTC
RemoteUrl: https://github.com/bioc/EMTscore
RemoteRef: HEAD
RemoteSha: 66ca8aebe6cfdea9e287c9751594618ade19c4a8
Packaged: 2026-10-11 15:53:47 UTC; root
Author: Haimei Wen [aut, cre] (ORCID: <https://orcid.org/0009-0006-1600-1210>),
  Daniel Lopez [aut],
  Tian Hong [aut],
  National Institutes of Health [fnd] (grant: R35GM149531),
  National Science Foundation [fnd] (grant: 2243562)
Maintainer: Haimei Wen <hudie.luoluo@gmail.com>