55 lines (54 with data), 2.2 kB
Package: TransProR
Type: Package
Title: Analysis and Visualization of Multi-Omics Data
Version: 1.0.4
Authors@R: person("Dongyue", "Yu", email = "yudongyue@mail.nankai.edu.cn", role = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0002-7041-2073"))
Maintainer: Dongyue Yu <yudongyue@mail.nankai.edu.cn>
Description: A tool for comprehensive transcriptomic data analysis, with a focus on transcript-level data preprocessing, expression profiling, differential expression analysis, and functional enrichment. It enables researchers to identify key biological processes, disease biomarkers, and gene regulatory mechanisms. 'TransProR' is aimed at researchers and bioinformaticians working with RNA-Seq data, providing an intuitive framework for in-depth analysis and visualization of transcriptomic datasets. The package includes comprehensive documentation and usage examples to guide users through the entire analysis pipeline. The differential expression analysis methods incorporated in the package include 'limma' (Ritchie et al., 2015, <doi:10.1093/nar/gkv007>; Smyth, 2005, <doi:10.1007/0-387-29362-0_23>), 'edgeR' (Robinson et al., 2010, <doi:10.1093/bioinformatics/btp616>), 'DESeq2' (Love et al., 2014, <doi:10.1186/s13059-014-0550-8>), and Wilcoxon tests (Li et al., 2022, <doi:10.1186/s13059-022-02648-4>), providing flexible and robust approaches to RNA-Seq data analysis. For more information, refer to the package vignettes and related publications.
Imports:
magrittr,
stats,
dplyr,
rlang,
tibble,
sva,
DESeq2,
utils,
edgeR,
limma,
ggplot2,
ggVennDiagram,
ggdensity,
ggpubr,
ggtree,
hrbrthemes,
grid,
ggraph,
tidygraph,
tidyr,
stringr,
geomtextpath,
ggalt,
ggnewscale,
Hmisc,
circlize,
graphics,
spiralize,
ComplexHeatmap,
grDevices
Suggests:
prettydoc,
knitr,
ggtreeExtra,
rmarkdown,
systemfonts
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/SSSYDYSSS/TransProRBook
BugReports: https://github.com/SSSYDYSSS/TransProR/issues
LazyData: true
RoxygenNote: 7.3.2
Depends:
R (>= 4.3.0)