To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DESeq")
In most cases, you don't need to download the package archive at all.
DESeq
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: Simon Anders, EMBL Heidelberg <sanders at fs.tum.de>
Maintainer: Simon Anders <sanders at fs.tum.de>
Citation (from within R,
enter citation("DESeq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DESeq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DESeq")
| R Script | Analysing RNA-Seq data with the "DESeq" package | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | ChIPSeq, DifferentialExpression, RNASeq, SAGE, Sequencing, Software |
| Version | 1.16.0 |
| In Bioconductor since | BioC 2.6 (R-2.11) |
| License | GPL (>= 3) |
| Depends | BiocGenerics(>= 0.7.5), Biobase(>= 2.21.7), locfit, lattice |
| Imports | genefilter, geneplotter, methods, MASS, RColorBrewer |
| Suggests | pasilla(>= 0.2.10), vsn, gplots |
| System Requirements | |
| URL | http://www-huber.embl.de/users/anders/DESeq |
| Depends On Me | DBChIP, EDDA, metaseqR, parathyroid, SeqGSEA, TCC, tRanslatome |
| Imports Me | ampliQueso, ArrayExpressHTS, easyRNASeq, EDASeq, EDDA, HTSFilter, rnaSeqMap |
| Suggests Me | BitSeq, compcodeR, DESeq2, dexus, DiffBind, EDASeq, ELBOW, gage, gCMAP, genefilter, GenomicAlignments, GenomicRanges, oneChannelGUI, pasilla, SSPA |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | DESeq_1.16.0.tar.gz |
| Windows Binary | DESeq_1.16.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | DESeq_1.16.0.tgz |
| Mac OS X 10.9 (Mavericks) | DESeq_1.16.0.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
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