DESCRIPTION

Package: LoveMangiola2022tidytranscriptomics
Title: Introduction to Tidy Transcriptomics
Version: 0.14.0
Authors@R: c(
    person("Maria", "Doyle", email="maria.doyle@petermac.org",
    role = c("aut"),
    comment = c(ORCID = "0000-0003-4847-8436")),
    person("Stefano", "Mangiola", email="mangiola.s@wehi.edu.au",
    role = c("aut","cre"),
    comment = c(ORCID = "0000-0001-7474-836X")))
Maintainer: Maria Doyle <maria.doyle@petermac.org>, Stefano Mangiola <mangiola.s@wehi.edu.au>
Description: This workshop will present how to perform analysis of RNA sequencing data following the tidy data paradigm, using the tidyseurat, tidySingleCellExperiment and tidyverse packages.
License: CC BY-SA 4.0 + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.1
Depends:
    R (>= 4.1.0)
Imports:
    tidySingleCellExperiment,
    tidyseurat,
    tidygate,
    Seurat,
    stats,
    utils,
    tibble,
    stringr,
    ggplot2,
    dplyr,
    readr,
    tidyr,
    purrr,
    forcats,
    ggrepel,
    plotly,
    igraph,
    broom,
    devtools,
    rlang,
    magrittr,
    R.utils,
    dittoSeq,
    tidybulk,
    tidySummarizedExperiment,
    glue
Suggests:
    knitr,
    rmarkdown,
    pkgdown
Biarch: true
biocViews: RNASeq, DifferentialExpression, GeneExpression, Normalization, Clustering, QualityControl, Sequencing, SingleCell, Transcription, Transcriptomics
URL: https://tidytranscriptomics-workshops.github.io/LoveMangiola2022_tidytranscriptomics/
BugReports: https://github.com/tidytranscriptomics-workshops/LoveMangiola2022_tidytranscriptomics/issues/new/choose
VignetteBuilder: knitr
DockerImage: ghcr.io/tidytranscriptomics-workshops/LoveMangiola2022_tidytranscriptomics:latest