# Empirical analysis of digital gene expression data in R

## Documentation for package ‘edgeR’ version 3.8.6

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E G L M N P Q R S T V W Z misc

edgeR-package | Empirical analysis of digital gene expression data in R

## -- A --

adjustedProfileLik | Adjusted Profile Likelihood for the Negative Binomial Dispersion Parameter
as.data.frame.TopTags | Turn a TopTags Object into a Dataframe
as.matrix.DGEList | Turn a DGEList Object into a Matrix
aveLogCPM | Average Log Counts Per Million
aveLogCPM.default | Average Log Counts Per Million
aveLogCPM.DGEGLM | Average Log Counts Per Million
aveLogCPM.DGEList | Average Log Counts Per Million

## -- B --

binMeanVar | Explore the mean-variance relationship for DGE data
binomTest | Exact Binomial Tests for Comparing Two Digital Libraries

## -- C --

calcNormFactors | Calculate Normalization Factors to Align Columns of a Count Matrix
calcNormFactors.default | Calculate Normalization Factors to Align Columns of a Count Matrix
calcNormFactors.DGEList | Calculate Normalization Factors to Align Columns of a Count Matrix
calcNormOffsetsforChIP | Normalize ChIP-Seq Read Counts to Input and Test for Enrichment
camera.DGEList | Competitive Gene Set Test for Digital Gene Expression Data Accounting for Inter-gene Correlation
commonCondLogLikDerDelta | Conditional Log-Likelihoods in Terms of Delta
condLogLikDerDelta | Conditional Log-Likelihood of the Dispersion for a Single Group of Replicate Libraries
condLogLikDerSize | Conditional Log-Likelihood of the Dispersion for a Single Group of Replicate Libraries
cpm | Counts per Million or Reads per Kilobase per Million
cpm.default | Counts per Million or Reads per Kilobase per Million
cpm.DGEList | Counts per Million or Reads per Kilobase per Million
cutWithMinN | Cut numeric vector into non-empty intervals

## -- D --

decideTestsDGE | Multiple Testing Across Genes and Contrasts
designAsFactor | Fit Negative Binomial Generalized Linear Model to Multiple Response Vectors: Low Level Functions
DGEExact-class | differential expression of Digital Gene Expression data - class
DGEGLM-class | Digital Gene Expression Generalized Linear Model results - class
DGEList | DGEList Constructor
DGEList-class | Digital Gene Expression data - class
DGELRT-class | Digital Gene Expression Likelihood Ratio Test data and results - class
dglmStdResid | Visualize the mean-variance relationship in DGE data using standardized residuals
diffSpliceDGE | Test for Differential Exon Usage
dim.DGEExact | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
dim.DGEGLM | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
dim.DGEList | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
dim.DGELRT | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
dim.TopTags | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
dimnames.DGEExact | Retrieve the Dimension Names of a DGE Object
dimnames.DGEGLM | Retrieve the Dimension Names of a DGE Object
dimnames.DGEList | Retrieve the Dimension Names of a DGE Object
dimnames.DGELRT | Retrieve the Dimension Names of a DGE Object
dimnames.TopTags | Retrieve the Dimension Names of a DGE Object
dimnames<-.DGEGLM | Retrieve the Dimension Names of a DGE Object
dimnames<-.DGEList | Retrieve the Dimension Names of a DGE Object
dispBinTrend | Estimate Dispersion Trend by Binning for NB GLMs
dispCoxReid | Estimate Common Dispersion for Negative Binomial GLMs
dispCoxReidInterpolateTagwise | Estimate Tagwise Dispersion for Negative Binomial GLMs by Cox-Reid Adjusted Profile Likelihood
dispCoxReidPowerTrend | Estimate Dispersion Trend for Negative Binomial GLMs
dispCoxReidSplineTrend | Estimate Dispersion Trend for Negative Binomial GLMs
dispDeviance | Estimate Common Dispersion for Negative Binomial GLMs
dispPearson | Estimate Common Dispersion for Negative Binomial GLMs

## -- E --

edgeR | Empirical analysis of digital gene expression data in R
edgeRUsersGuide | View edgeR User's Guide
equalizeLibSizes | Equalize Library Sizes by Quantile-to-Quantile Normalization
estimateCommonDisp | Estimate Common Negative Binomial Dispersion by Conditional Maximum Likelihood
estimateDisp | Estimate Common, Trended and Tagwise Negative Binomial dispersions by weighted likelihood empirical Bayes
estimateExonGenewiseDisp | Estimate Genewise Dispersions from Exon-Level Count Data
estimateGLMCommonDisp | Estimate Common Dispersion for Negative Binomial GLMs
estimateGLMCommonDisp.default | Estimate Common Dispersion for Negative Binomial GLMs
estimateGLMCommonDisp.DGEList | Estimate Common Dispersion for Negative Binomial GLMs
estimateGLMRobustDisp | Empirical Robust Bayes Tagwise Dispersions for Negative Binomial GLMs using Observation Weights
estimateGLMTagwiseDisp | Empirical Bayes Tagwise Dispersions for Negative Binomial GLMs
estimateGLMTagwiseDisp.default | Empirical Bayes Tagwise Dispersions for Negative Binomial GLMs
estimateGLMTagwiseDisp.DGEList | Empirical Bayes Tagwise Dispersions for Negative Binomial GLMs
estimateGLMTrendedDisp | Estimate Trended Dispersion for Negative Binomial GLMs
estimateGLMTrendedDisp.default | Estimate Trended Dispersion for Negative Binomial GLMs
estimateGLMTrendedDisp.DGEList | Estimate Trended Dispersion for Negative Binomial GLMs
estimateTagwiseDisp | Estimate Empirical Bayes Tagwise Dispersion Values
estimateTrendedDisp | Estimate Empirical Bayes Trended Dispersion Values
exactTest | Exact Tests for Differences between Two Groups of Negative-Binomial Counts
exactTestBetaApprox | Exact Tests for Differences between Two Groups of Negative-Binomial Counts
exactTestByDeviance | Exact Tests for Differences between Two Groups of Negative-Binomial Counts
exactTestBySmallP | Exact Tests for Differences between Two Groups of Negative-Binomial Counts
exactTestDoubleTail | Exact Tests for Differences between Two Groups of Negative-Binomial Counts
expandAsMatrix | expandAsMatrix

## -- G --

getCounts | Extract Specified Component of a DGEList Object
getDispersion | Extract Specified Component of a DGEList Object
getDispersions | Visualize the mean-variance relationship in DGE data using standardized residuals
getOffset | Extract Specified Component of a DGEList Object
getPriorN | Get a Recommended Value for Prior N from DGEList Object
glmFit | Genewise Negative Binomial Generalized Linear Models
glmFit.default | Genewise Negative Binomial Generalized Linear Models
glmFit.DGEList | Genewise Negative Binomial Generalized Linear Models
glmLRT | Genewise Negative Binomial Generalized Linear Models
glmQLFit | Quasi-likelihood methods with empirical Bayes shrinkage
glmQLFTest | Quasi-likelihood methods with empirical Bayes shrinkage
goana.DGEExact | Gene Ontology Analysis of Differentially Expressed Genes
goana.DGELRT | Gene Ontology Analysis of Differentially Expressed Genes
gof | Goodness of Fit Tests for Multiple GLM Fits
goodTuring | Good-Turing Frequency Estimation
goodTuringPlot | Good-Turing Frequency Estimation
goodTuringProportions | Good-Turing Frequency Estimation

## -- L --

length.DGEExact | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
length.DGEGLM | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
length.DGEList | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
length.DGELRT | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
length.TopTags | Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object
locfitByCol | Locally Weighted Mean By Column
loessByCol | Locally Weighted Mean By Column

## -- M --

maPlot | Plots Log-Fold Change versus Log-Concentration (or, M versus A) for Count Data
maximizeInterpolant | Maximize a function given a table of values by spline interpolation.
maximizeQuadratic | Maximize a function given a table of values by quadratic interpolation.
mglm | Fit Negative Binomial Generalized Linear Model to Multiple Response Vectors: Low Level Functions
mglmLevenberg | Fit Negative Binomial Generalized Linear Model to Multiple Response Vectors: Low Level Functions
mglmOneGroup | Fit Negative Binomial Generalized Linear Model to Multiple Response Vectors: Low Level Functions
mglmOneWay | Fit Negative Binomial Generalized Linear Model to Multiple Response Vectors: Low Level Functions
movingAverageByCol | Moving Average Smoother of Matrix Columns
mroast.DGEList | Rotation Gene Set Tests for Digital Gene Expression Data

## -- N --

nbinomDeviance | Negative Binomial Deviance
nbinomUnitDeviance | Negative Binomial Deviance
normalizeChIPtoInput | Normalize ChIP-Seq Read Counts to Input and Test for Enrichment

## -- P --

plotBCV | Plot Biological Coefficient of Variation
plotExonUsage | Create a Plot of Exon Usage from Exon-Level Count Data
plotMDS.DGEList | Multidimensional scaling plot of distances between digital gene expression profiles
plotMeanVar | Explore the mean-variance relationship for DGE data
plotQLDisp | Plot the quasi-likelihood dispersion
plotSmear | Plots log-Fold Change versus log-Concentration (or, M versus A) for Count Data
plotSpliceDGE | Plot exons on differentially spliced gene
predFC | Predictive log-fold changes
predFC.default | Predictive log-fold changes
predFC.DGEList | Predictive log-fold changes
processAmplicons | Process raw data from pooled genetic sequencing screens

## -- Q --

q2qnbinom | Quantile to Quantile Mapping between Negative-Binomial Distributions
q2qpois | Quantile to Quantile Mapping between Negative-Binomial Distributions

## -- R --

readDGE | Read and Merge a Set of Files Containing DGE Data
roast.DGEList | Rotation Gene Set Tests for Digital Gene Expression Data
rpkm | Counts per Million or Reads per Kilobase per Million
rpkm.default | Counts per Million or Reads per Kilobase per Million
rpkm.DGEList | Counts per Million or Reads per Kilobase per Million

## -- S --

show-method | differential expression of Digital Gene Expression data - class
show-method | Digital Gene Expression Generalized Linear Model results - class
show-method | Digital Gene Expression Likelihood Ratio Test data and results - class
show-method | Table of the Top Differentially Expressed Tags
spliceVariants | Identify Genes with Splice Variants
splitIntoGroups | Split the Counts or Pseudocounts from a DGEList Object According To Group
splitIntoGroupsPseudo | Split the Counts or Pseudocounts from a DGEList Object According To Group
subsetting | Subset DGEList, DGEGLM, DGEExact and DGELRT Objects
sumTechReps | Sum Over Replicate Samples
sumTechReps.default | Sum Over Replicate Samples
sumTechReps.DGEList | Sum Over Replicate Samples
systematicSubset | Take a systematic subset of indices.

## -- T --

thinCounts | Binomial or Multinomial Thinning of Counts
topSpliceDGE | Top table of differentially spliced genes or exons
topTags | Table of the Top Differentially Expressed Tags
TopTags-class | Table of the Top Differentially Expressed Tags
treatDGE | Testing for Differential Expression Relative to a Threshold

## -- V --

validDGEList | Check for Valid DGEList object

## -- W --

weightedCondLogLikDerDelta | Weighted Conditional Log-Likelihood in Terms of Delta
WLEB | Calculate Weighted Likelihood Empirical Bayes Estimates

## -- Z --

zscoreNBinom | Z-score Equivalents of Negative Binomial Deviate

## -- misc --

[.DGEExact | Subset DGEList, DGEGLM, DGEExact and DGELRT Objects
[.DGEGLM | Subset DGEList, DGEGLM, DGEExact and DGELRT Objects
[.DGEList | Subset DGEList, DGEGLM, DGEExact and DGELRT Objects
[.DGELRT | Subset DGEList, DGEGLM, DGEExact and DGELRT Objects
[.TopTags | Subset DGEList, DGEGLM, DGEExact and DGELRT Objects