To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DESeq2")
In most cases, you don't need to download the package archive at all.
DESeq2
Differential gene expression analysis based on the negative binomial distribution
Bioconductor version: 2.14
Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution
Author: Michael Love (HSPH Boston), Simon Anders, Wolfgang Huber (EMBL Heidelberg)
Maintainer: Michael Love <michaelisaiahlove at gmail.com>
Citation (from within R,
enter citation("DESeq2")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DESeq2")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DESeq2")
| R Script | Analyzing RNA-Seq data with the "DESeq2" package | |
| R Script | Beginner's guide to the "DESeq2" package | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | ChIPSeq, DifferentialExpression, RNASeq, SAGE, Sequencing, Software |
| Version | 1.4.5 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | GPL (>= 3) |
| Depends | GenomicRanges, IRanges, Rcpp (>= 0.10.1), RcppArmadillo (>= 0.3.4.4) |
| Imports | BiocGenerics(>= 0.7.5), methods, locfit, genefilter, geneplotter, RColorBrewer, lattice |
| Suggests | RUnit, gplots, knitr, Biobase, BiocStyle, parathyroidSE, pasilla(>= 0.2.10), DESeq, vsn, GenomicAlignments, GenomicFeatures, Rsamtools, biomaRt |
| System Requirements | |
| URL | |
| Depends On Me | DEXSeq, MLSeq, TCC |
| Imports Me | HTSFilter, phyloseq, ReportingTools |
| Suggests Me | BiocGenerics, compcodeR, DiffBind, gage |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | DESeq2_1.4.5.tar.gz |
| Windows Binary | DESeq2_1.4.5.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | DESeq2_1.4.5.tgz |
| Mac OS X 10.9 (Mavericks) | DESeq2_1.4.5.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
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