To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DEGseq")
In most cases, you don't need to download the package archive at all.
DEGseq
Identify Differentially Expressed Genes from RNA-seq data
Bioconductor version: 3.0
DEGseq is an R package to identify differentially expressed genes from RNA-Seq data.
Author: Likun Wang <wanglk at hsc.pku.edu.cn> and Xi Wang <wang-xi05 at mails.tsinghua.edu.cn>.
Maintainer: Likun Wang <wanglk at hsc.pku.edu.cn>
Citation (from within R,
enter citation("DEGseq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DEGseq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DEGseq")
| R Script | DEGseq | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, GeneExpression, Preprocessing, RNASeq, Software |
| Version | 1.20.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) |
| License | LGPL (>=2) |
| Depends | R (>= 2.8.0), qvalue, samr, methods |
| Imports | graphics, grDevices, methods, stats, utils |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | DEGseq_1.20.0.tar.gz |
| Windows Binary | DEGseq_1.20.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | DEGseq_1.20.0.tgz |
| Mac OS X 10.9 (Mavericks) | DEGseq_1.20.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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