Differential analysis of RNA-seq incorporating quantification uncertainty
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Updated: Mar 1, 2026

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Published on: September 18, 2021
Harold Pimentel1, Nicolas L Bray2, Suzette Puente3
1Department of Computer Science, University of California, Berkeley, Berkeley, California, USA.
Abstract:
We describe sleuth (http://pachterlab.github.io/sleuth), a method for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance. sleuth is implemented in an interactive shiny app that utilizes kallisto quantifications and bootstraps for fast and accurate analysis of data from RNA-seq experiments.
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