DESeq
Digital gene expresion analysis based on the negative binomial distribution
Bioconductor version: 2.7
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>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DESeq")
To cite this package in a publication, start R and enter:
citation("DESeq")
Documentation
| R Script | Analysing RNA-Seq data with the "DESeq" package | |
| Reference Manual |
Details
| biocViews | HighThroughputSequencing, ChIPseq, RNAseq, SAGE, DifferentialExpression |
| Depends | Biobase, locfit |
| Imports | genefilter, geneplotter, methods |
| Suggests | |
| System Requirements | |
| License | GPL (>= 3) |
| URL | http://www-huber.embl.de/users/anders/DESeq/ |
| Depends On Me | |
| Imports Me | rnaSeqMap |
| Suggests Me | |
| Version | 1.2.1 |
| Since | Bioconductor 2.6 (R-2.11) |
Package Downloads
| Package Source | DESeq_1.2.1.tar.gz |
| Windows Binary | DESeq_1.2.1.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | DESeq_1.2.1.tgz |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
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