DEGseq
This is thereleased version of DEGseq; for the devel version, seeDEGseq.
Identify Differentially Expressed Genes from RNA-seq data
Bioconductor version: Release (3.22)
DEGseq is an R package to identify differentially expressed genes from RNA-Seq data.
Author: Likun Wang <wanglk at pku.edu.cn>, Xiaowo Wang <xwwang at tsinghua.edu.cn> and Xuegong Zhang <zhangxg at tsinghua.edu.cn>.
Maintainer: Likun Wang <wanglk at pku.edu.cn>
Citation (from within R, enter
citation("DEGseq")):Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")BiocManager::install("DEGseq")For older versions of R, please refer to the appropriateBioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DEGseq")| DEGseq | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DifferentialExpression,GeneExpression,ImmunoOncology,Preprocessing,RNASeq,Software |
| Version | 1.64.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) (16 years) |
| License | LGPL (>=2) |
| Depends | R (>= 2.8.0),qvalue, methods |
| Imports | graphics, grDevices, methods, stats, utils |
| System Requirements | |
| URL |
See More
| Suggests | |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
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| Links To Me | |
| Build Report | Build Report |
Package Archives
FollowInstallation instructions to use this package in your R session.
| Source Package | DEGseq_1.64.0.tar.gz |
| Windows Binary (x86_64) | DEGseq_1.64.0.zip |
| macOS Binary (x86_64) | DEGseq_1.64.0.tgz |
| macOS Binary (arm64) | DEGseq_1.64.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/DEGseq |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/DEGseq |
| Bioc Package Browser | https://code.bioconductor.org/browse/DEGseq/ |
| Package Short Url | https://bioconductor.org/packages/DEGseq/ |
| Package Downloads Report | Download Stats |