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edgeR | A Bioconductor package for differential expression analysis of digital gene expression data

Allows differential expression analysis of digital gene expression data. edgeR implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi likelihood tests. The package and methods are general, and can work on other sources of count data, such as barcoding experiments and peptide counts.

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edgeR forum

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edgeR classification

edgeR specifications

Unique identifier:
OMICS_01308
Software type:
Package/Module
Restrictions to use:
None
Programming languages:
R
Computer skills:
Advanced
Stability:
Stable
Maintained:
Yes
Name:
empirical analysis of DGE in R
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
GNU General Public License version 2.0
Version:
3.10.2
Requirements:
limma

edgeR distribution

versioning

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edgeR support

Documentation

Additional information

http://www.bioconductor.org/packages/release/bioc/manuals/edgeR/man/edgeR.pdf

Credits

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Publications

Institution(s)

Cancer Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia

Funding source(s)

Supported by National Health and Medical Research Council Program (Grant 406657), NHMRC, Independent Research Institutes Infrastructure Support Scheme (Grant 361646), Victorian State Government OIS grant, a Melbourne International Research Scholarship, Belz, Harris and IBS Honours scholarships.

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