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 (>= 4.6.0)
git_url: https://git.bioconductor.org/packages/EMTscore
git_branch: devel
git_last_commit: 66ca8ae
git_last_commit_date: 2026-08-04
Repository: Bioconductor 3.24
Date/Publication: 2026-08-09
Packaged: 2026-08-09 21:00:46 UTC; biocbuild
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>
Built: R 4.6.1; ; 2026-08-10 05:47:39 UTC; unix
