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 read counts, including ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE and CAGE.
|Author||Yunshun Chen, Aaron TL Lun, Davis J McCarthy, Matthew E Ritchie, Belinda Phipson, Yifang Hu, Xiaobei Zhou, Mark D Robinson, Gordon K Smyth|
|Bioconductor views||AlternativeSplicing BatchEffect Bayesian BiomedicalInformatics CellBiology ChIPSeq Clustering Coverage DNAMethylation DifferentialExpression DifferentialMethylation DifferentialSplicing Epigenetics FunctionalGenomics GeneExpression GeneSetEnrichment Genetics ImmunoOncology MultipleComparison Normalization Pathways QualityControl RNASeq Regression SAGE Sequencing SystemsBiology TimeCourse Transcription Transcriptomics|
|Maintainer||Yunshun Chen <firstname.lastname@example.org>, Gordon Smyth <email@example.com>, Aaron Lun <firstname.lastname@example.org>, Mark Robinson <email@example.com>|
|Package repository||View on GitHub|
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