Package: DESeq2 1.47.1

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], Kwame Forbes [ctb], Simon Anders [aut, ctb], Wolfgang Huber [aut, ctb], RADIANT EU FP7 [fnd], NIH NHGRI [fnd], CZI [fnd]

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NEWS

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

Peer review:

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

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

On BioConductor:DESeq2-1.47.1(bioc 3.21)DESeq2-1.46.0(bioc 3.20)

sequencingrnaseqchipseqgeneexpressiontranscriptionnormalizationdifferentialexpressionbayesianregressionprincipalcomponentclusteringimmunooncologyopenblascpp

16.00 score 365 stars 118 packages 16k scripts 37k downloads 9.6k mentions 58 exports 66 dependencies

Last updated 1 months agofrom:30cc350d58. Checks:OK: 7 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 15 2024
R-4.5-win-x86_64NOTEDec 15 2024
R-4.5-linux-x86_64NOTEDec 15 2024
R-4.4-win-x86_64OKDec 15 2024
R-4.4-mac-x86_64OKDec 15 2024
R-4.4-mac-aarch64OKDec 15 2024
R-4.3-win-x86_64OKDec 15 2024
R-4.3-mac-x86_64OKDec 15 2024
R-4.3-mac-aarch64OKDec 15 2024

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

Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelclicodetoolscolorspacecpp11crayoncurlDelayedArrayfansifarverformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobandjsonlitelabelinglambda.rlatticelifecyclelocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangS4ArraysS4VectorsscalessnowSparseArraySummarizedExperimentsystibbleUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc

Analyzing RNA-seq data with DESeq2

Michael I. Love, Simon Anders, and Wolfgang Huber

Rendered fromDESeq2.Rmdusingknitr::rmarkdownon Dec 15 2024.

Last update: 2024-11-14
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
Integrate bulk DE results with Bioconductor single-cell RNA-seq datasetsintegrateWithSingleCell
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