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    edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

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    12961
    Author
    Robinson, MD; McCarthy, DJ; Smyth, GK
    Date
    2010-01-01
    Source Title
    Bioinformatics
    Publisher
    OXFORD UNIV PRESS
    University of Melbourne Author/s
    Smyth, Gordon; McCarthy, Davis
    Affiliation
    School of Mathematics and Statistics
    Metadata
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    Document Type
    Journal Article
    Citations
    Robinson, M. D., McCarthy, D. J. & Smyth, G. K. (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. BIOINFORMATICS, 26 (1), pp.139-140. https://doi.org/10.1093/bioinformatics/btp616.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/259114
    DOI
    10.1093/bioinformatics/btp616
    Abstract
    SUMMARY: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. AVAILABILITY: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).

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