Differential expression analysis based on the Negative Binomial (a.k.a. Gamma-Poisson) distribution
DESeq2 package for differential analysis of count data
DESeqDataSet object and constructors
DESeqResults object and constructor
DESeqTransform object and constructor
Extract a matrix of model coefficients/standard errors
Collapse technical replicates in a RangedSummarizedExperiment or DESeqDataSet
Accessors for the 'counts' slot of a DESeqDataSet object.
Accessors for the 'design' slot of a DESeqDataSet object.
Accessors for the 'dispersionFunction' slot of a DESeqDataSet object.
Accessor functions for the dispersion estimates in a DESeqDataSet object.
Steps for estimating the beta prior variance
Estimate the dispersions for a DESeqDataSet
Low-level functions to fit dispersion estimates
Estimate the size factors for a 'DESeqDataSet'
Low-level function to estimate size factors with robust regression.
FPKM: fragments per kilobase per million mapped fragments
FPM: fragments per million mapped fragments
Shrink log2 fold changes
Make a simulated DESeqDataSet
Likelihood ratio test (chi-squared test) for GLMs
Wald test for the GLM coefficients
Normalized counts transformation
Accessor functions for the normalization factors in a DESeqDataSet object.
Normalize for gene length
Plot of normalized counts for a single gene
Plot dispersion estimates
MA-plot from base means and log fold changes
Sample PCA plot for transformed data
Sparsity plot
Accessors for the 'priorInfo' slot of a DESeqResults object.
Replace outliers with trimmed mean
Extract results from a DESeq analysis
Apply a 'regularized log' transformation
Show method for DESeqResults objects
Accessor functions for the 'sizeFactors' information in a DESeqDataSet object.
Summarize DESeq results
Unmix samples using loss in a variance stabilized space
Apply a variance stabilizing transformation (VST) to the count data
Quickly estimate dispersion trend and apply a variance stabilizing transformation