Differential expression analysis of RNA-seq expression profiles with biological replication. 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. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, SAGE and CAGE.
|Author||Yunshun Chen <firstname.lastname@example.org>, Aaron Lun <email@example.com>, Davis McCarthy <firstname.lastname@example.org>, Xiaobei Zhou <email@example.com>, Mark Robinson <firstname.lastname@example.org>, Gordon Smyth <email@example.com>|
|Bioconductor views||AlternativeSplicing BatchEffect Bayesian ChIPSeq Clustering Coverage DifferentialExpression DifferentialSplicing GeneExpression GeneSetEnrichment Genetics MultipleComparison Normalization QualityControl RNASeq Regression SAGE Sequencing TimeCourse Transcription|
|Maintainer||Yunshun Chen <firstname.lastname@example.org>, Aaron Lun <email@example.com>, Mark Robinson <firstname.lastname@example.org>, Davis McCarthy <email@example.com>, Gordon Smyth <firstname.lastname@example.org>|
|Package repository||View on Bioconductor|
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