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DESCRIPTION
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DESCRIPTION
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Package: zhejiang2020
Title: Introduction to Tidy Transcriptomics
Version: 0.3.3
Authors@R: c(
person("Xueyi", "Dong", email="dong.x@wehi.edu.au",
role = c("aut")),
person("Luyi", "Tian", email="tian.l@wehi.edu.au",
role = c("aut")),
person("Yue", "You", email="you.y@wehi.edu.au",
role = c("aut")),
person("Stefano", "Mangiola", email="mangiola.s@wehi.edu.au",
role = c("aut","cre"),
comment = c(ORCID = "0000-0001-7474-836X")),
person("Maria", "Doyle", email = "Maria.Doyle@petermac.org",
role = c("ctb"))
)
Maintainer: 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 tidybulk, tidySingleCellExperiment, tidyHeatmap and tidyverse packages.
License: CC BY-SA 4.0 + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Depends:
R (>= 4.0.1)
Imports:
tidybulk,
tidySingleCellExperiment,
scater,
scran,
stats,
utils,
tibble,
stringr,
ggplot2,
dplyr,
readr,
tidyr,
purrr,
limma,
edgeR,
ggrepel,
dittoSeq,
SingleR,
R.utils,
SummarizedExperiment,
SingleCellExperiment,
igraph,
Glimma,
Mus.musculus,
Biobase,
DropletUtils,
EnsDb.Hsapiens.v86,
RColorBrewer,
pheatmap,
batchelor,
TENxPBMCData,
Rtsne,
igraph,
celldex,
gplots,
RNAseq123,
ggbeeswarm,
uwot
Suggests:
knitr,
rmarkdown,
pkgdown,
BiocStyle
Biarch: true
biocViews: RNASeq, DifferentialExpression, GeneExpression, Normalization, Clustering, QualityControl, Sequencing, SingleCell, Transcription, Transcriptomics
URL: https://stemangiola.github.io/zhejiang2020/
BugReports: https://github.com/stemangiola/zhejiang2020/issues/new/choose
VignetteBuilder: knitr
DockerImage: stemangiola/zhejiang2020:zhejiang2020