Learn R Programming

DESeq2 (version 1.12.3)

Differential gene expression analysis based on the negative binomial distribution

Description

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.

Copy Link

Version

Version

1.12.3

License

LGPL (>= 3)

Maintainer

Michael Love

Last Published

February 15th, 2017

Functions in DESeq2 (1.12.3)

DESeq2-package

DESeq2 package for differential analysis of count data
normTransform

Normalized counts transformation
estimateBetaPriorVar

Steps for estimating the beta prior variance
plotPCA

Sample PCA plot for transformed data
plotCounts

Plot of normalized counts for a single gene on log scale
fpm

FPM: fragments per million mapped fragments
replaceOutliers

Replace outliers with trimmed mean
estimateDispersionsGeneEst

Low-level functions to fit dispersion estimates
plotSparsity

Sparsity plot
DESeqTransform-class

DESeqTransform object and constructor
makeExampleDESeqDataSet

Make a simulated DESeqDataSet
nbinomLRT

Likelihood ratio test (chi-squared test) for GLMs
dispersions

Accessor functions for the dispersion estimates in a DESeqDataSet object.
counts

Accessors for the 'counts' slot of a DESeqDataSet object.
estimateSizeFactors

Estimate the size factors for a DESeqDataSet
summary

Summarize DESeq results
collapseReplicates

Collapse technical replicates in a RangedSummarizedExperiment or DESeqDataSet
DESeqResults-class

DESeqResults object and constructor
normalizeGeneLength

Normalize for gene length
estimateDispersions

Estimate the dispersions for a DESeqDataSet
plotDispEsts

Plot dispersion estimates
results

Extract results from a DESeq analysis
show

Show method for DESeqResults objects
sizeFactors

Accessor functions for the 'sizeFactors' information in a DESeqDataSet object.
estimateSizeFactorsForMatrix

Low-level function to estimate size factors with robust regression.
design

Accessors for the 'design' slot of a DESeqDataSet object.
DESeq

Differential expression analysis based on the Negative Binomial (a.k.a. Gamma-Poisson) distribution
fpkm

FPKM: fragments per kilobase per million mapped fragments
rlog

Apply a 'regularized log' transformation
normalizationFactors

Accessor functions for the normalization factors in a DESeqDataSet object.
vst

Quickly estimate dispersion trend and apply a variance stabilizing transformation
coef

Extract a matrix of model coefficients/standard errors
DESeqDataSet-class

DESeqDataSet object and constructors
dispersionFunction

Accessors for the 'dispersionFunction' slot of a DESeqDataSet object.
plotMA

MA-plot from base means and log fold changes
nbinomWaldTest

Wald test for the GLM coefficients
varianceStabilizingTransformation

Apply a variance stabilizing transformation (VST) to the count data