Open Access
Open access
volume 11, issue 10, publication number R106

Differential expression analysis for sequence count data

Anders Simon 1
Huber Wolfgang 1
1
 
European Molecular Biology Laboratory, heidelberg, Germany
Publication typeJournal Article
Publication date2010-10-28
Abstract
High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.

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