DESCRIPTION

Package: vissE
Title: Visualising Set Enrichment Analysis Results
Version: 1.11.1
Authors@R: c(
            person(given = "Dharmesh D.",
                   family = "Bhuva",
                   role = c("aut", "cre"),
                   email = "bhuva.d@wehi.edu.au",
                   comment = c(ORCID = "0000-0002-6398-9157")),
            person(given = "Ahmed",
                   family = "Mohamed",
                   role = c("ctb"),
                   email = "mohamed.a@wehi.edu.au")
            )
Description: This package enables the interpretation and analysis of results from a gene set enrichment analysis using network-based and text-mining approaches. Most enrichment analyses result in large lists of significant gene sets that are difficult to interpret. Tools in this package help build a similarity-based network of significant gene sets from a gene set enrichment analysis that can then be investigated for their biological function using text-mining approaches.
biocViews: Software, GeneExpression, GeneSetEnrichment, NetworkEnrichment, Network
License: GPL-3
Encoding: UTF-8
LazyDataCompression: bzip2
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Depends: 
    R (>= 4.1)
Imports: 
    igraph,
    methods,
    plyr,
    ggplot2,
    scico,
    RColorBrewer,
    tm,
    ggwordcloud,
    GSEABase,
    reshape2,
    grDevices,
    ggforce,
    msigdb,
    ggrepel,
    textstem,
    tidygraph,
    stats,
    scales,
    ggraph
Suggests: 
    testthat,
    org.Hs.eg.db,
    org.Mm.eg.db,
    patchwork,
    singscore,
    knitr,
    rmarkdown,
    prettydoc,
    BiocStyle,
    pkgdown,
    covr
URL: https://davislaboratory.github.io/vissE
BugReports: https://github.com/DavisLaboratory/vissE/issues
VignetteBuilder: knitr