Package: DESeq2 1.53.0

Michael Love

DESeq2: Differential gene expression analysis based on the negative binomial distribution

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Authors:Michael Love [aut, cre], Constantin Ahlmann-Eltze [ctb], Anqi Zhu [ctb], Nikolaos Ignatiadis [ctb], Raphael Rossellini [ctb], Kwame Forbes [ctb], Simon Anders [aut, ctb], Wolfgang Huber [aut, ctb], RADIANT EU FP7 [fnd], NIH NHGRI [fnd], CZI [fnd]

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card.svg |card.png
DESeq2/json (API)
NEWS

# Install 'DESeq2' in R:
install.packages('DESeq2', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/thelovelab/deseq2/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On BioConductor:DESeq2-1.53.0(bioc 3.24)DESeq2-1.52.0(bioc 3.23)

sequencingrnaseqchipseqgeneexpressiontranscriptionnormalizationdifferentialexpressionbayesianregressionprincipalcomponentclusteringimmunooncologyopenblascpp

16.67 score 461 stars 123 packages 26k scripts 45k downloads 9.6k mentions 57 exports 45 dependencies

Last updated from:e0580b8596. Checks:1 ERROR, 11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR277
linux-devel-arm64NOTE446
linux-devel-x86_64NOTE495
source / vignettesOK400
linux-release-arm64NOTE477
linux-release-x86_64NOTE362
macos-release-arm64NOTE267
macos-release-x86_64NOTE842
macos-oldrel-arm64NOTE271
macos-oldrel-x86_64NOTE666
windows-develNOTE496
windows-releaseNOTE485
windows-oldrelNOTE473
wasm-releaseOK224

Exports:collapseReplicatescountscounts<-DESeqDESeqDataSetDESeqDataSetFromHTSeqCountDESeqDataSetFromMatrixDESeqDataSetFromTximportDESeqResultsDESeqTransformdesigndesign<-dispersionFunctiondispersionFunction<-dispersionsdispersions<-estimateBetaPriorVarestimateDispersionsestimateDispersionsFitestimateDispersionsGeneEstestimateDispersionsMAPestimateDispersionsPriorVarestimateMLEForBetaPriorVarestimateSizeFactorsestimateSizeFactorsForMatrixfpkmfpmgetVarianceStabilizedDatalfcShrinkmakeExampleDESeqDataSetnbinomLRTnbinomWaldTestnormalizationFactorsnormalizationFactors<-normalizeGeneLengthnormTransformplotCountsplotDispEstsplotMAplotPCAplotSparsitypriorInfopriorInfo<-removeResultsreplaceOutliersreplaceOutliersWithTrimmedMeanresultsresultsNamesrlogrlogTransformationshowsizeFactorssizeFactors<-summaryunmixvarianceStabilizingTransformationvst

Dependencies:abindBHBiobaseBiocGenericsBiocParallelclicodetoolscpp11DelayedArrayfarverformatRfutile.loggerfutile.optionsgenericsGenomicRangesggplot2gluegtableIRangesisobandlabelinglambda.rlatticelifecyclelocfitMatrixMatrixGenericsmatrixStatsR6RColorBrewerRcppRcppArmadillorlangS4ArraysS4VectorsS7scalesSeqinfosnowSparseArraySummarizedExperimentvctrsviridisLitewithrXVector

Analyzing RNA-seq data with DESeq2

Rendered fromDESeq2.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-11-18
Started: 2016-11-18

Readme and manuals

Help Manual

Help pageTopics
DESeq2 package for differential analysis of count dataDESeq2-package DESeq2
Extract a matrix of model coefficients/standard errorscoef.DESeqDataSet
Collapse technical replicates in a RangedSummarizedExperiment or DESeqDataSetcollapseReplicates
Accessors for the 'counts' slot of a DESeqDataSet object.counts,DESeqDataSet-method counts<-,DESeqDataSet,matrix-method
Differential expression analysis based on the Negative Binomial (a.k.a. Gamma-Poisson) distributionDESeq
DESeqDataSet object and constructorsDESeqDataSet DESeqDataSet-class DESeqDataSetFromHTSeqCount DESeqDataSetFromMatrix DESeqDataSetFromTximport
DESeqResults object and constructorDESeqResults DESeqResults-class
DESeqTransform object and constructorDESeqTransform DESeqTransform-class
Accessors for the 'design' slot of a DESeqDataSet object.design,DESeqDataSet-method design<-,DESeqDataSet,formula-method design<-,DESeqDataSet,matrix-method
Accessors for the 'dispersionFunction' slot of a DESeqDataSet object.dispersionFunction dispersionFunction,DESeqDataSet-method dispersionFunction<- dispersionFunction<-,DESeqDataSet,function-method
Accessor functions for the dispersion estimates in a DESeqDataSet object.dispersions dispersions,DESeqDataSet-method dispersions<- dispersions<-,DESeqDataSet,numeric-method
Steps for estimating the beta prior varianceestimateBetaPriorVar estimateMLEForBetaPriorVar
Estimate the dispersions for a DESeqDataSetestimateDispersions,DESeqDataSet-method
Low-level functions to fit dispersion estimatesestimateDispersionsFit estimateDispersionsGeneEst estimateDispersionsMAP estimateDispersionsPriorVar
Estimate the size factors for a 'DESeqDataSet'estimateSizeFactors,DESeqDataSet-method
Low-level function to estimate size factors with robust regression.estimateSizeFactorsForMatrix
FPKM: fragments per kilobase per million mapped fragmentsfpkm
FPM: fragments per million mapped fragmentsfpm
Shrink log2 fold changeslfcShrink
Make a simulated DESeqDataSetmakeExampleDESeqDataSet
Likelihood ratio test (chi-squared test) for GLMsnbinomLRT
Wald test for the GLM coefficientsnbinomWaldTest
Accessor functions for the normalization factors in a DESeqDataSet object.normalizationFactors normalizationFactors,DESeqDataSet-method normalizationFactors<- normalizationFactors<-,DESeqDataSet,matrix-method
Normalize for gene lengthnormalizeGeneLength
Normalized counts transformationnormTransform
Plot of normalized counts for a single geneplotCounts
Plot dispersion estimatesplotDispEsts plotDispEsts,DESeqDataSet-method
MA-plot from base means and log fold changesplotMA plotMA,DESeqDataSet-method plotMA,DESeqResults-method
Sample PCA plot for transformed dataplotPCA plotPCA,DESeqTransform-method
Sparsity plotplotSparsity
Accessors for the 'priorInfo' slot of a DESeqResults object.priorInfo priorInfo,DESeqResults-method priorInfo<- priorInfo<-,DESeqResults,list-method
Replace outliers with trimmed meanreplaceOutliers replaceOutliersWithTrimmedMean
Extract results from a DESeq analysisremoveResults results resultsNames
Apply a 'regularized log' transformationrlog rlogTransformation
Show method for DESeqResults objectsshow,DESeqResults-method
Accessor functions for the 'sizeFactors' information in a DESeqDataSet object.sizeFactors,DESeqDataSet-method sizeFactors<-,DESeqDataSet,numeric-method
Summarize DESeq resultssummary,DESeqResults-method
Unmix samples using loss in a variance stabilized spaceunmix
Apply a variance stabilizing transformation (VST) to the count datagetVarianceStabilizedData varianceStabilizingTransformation
Quickly estimate dispersion trend and apply a variance stabilizing transformationvst