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edgeR (version 3.8.6)

Empirical analysis of digital gene expression data in R

Description

Differential expression analysis of RNA-seq and digital gene expression profiles with biological replication. Uses empirical Bayes estimation and exact tests based on the negative binomial distribution. Also useful for differential signal analysis with other types of genome-scale count data.

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Version

Version

3.8.6

License

GPL (>=2)

Maintainer

Yunshun Chen

Last Published

February 15th, 2017

Functions in edgeR (3.8.6)

adjustedProfileLik

Adjusted Profile Likelihood for the Negative Binomial Dispersion Parameter

estimateTrendedDisp

Estimate Empirical Bayes Trended Dispersion Values

Turn a TopTags Object into a Dataframe

differential expression of Digital Gene Expression data - class

equalizeLibSizes

Equalize Library Sizes by Quantile-to-Quantile Normalization

edgeRUsersGuide

View edgeR User's Guide

Digital Gene Expression Generalized Linear Model results - class

Exact Tests for Differences between Two Groups of Negative-Binomial Counts

Plots Log-Fold Change versus Log-Concentration (or, M versus A) for Count Data

Locally Weighted Mean By Column

Fit Negative Binomial Generalized Linear Model to Multiple Response Vectors: Low Level Functions

Explore the mean-variance relationship for DGE data

Plot exons on differentially spliced gene

Retrieve the Dimensions of a DGEList, DGEExact, DGEGLM, DGELRT or TopTags Object

estimateCommonDisp

Estimate Common Negative Binomial Dispersion by Conditional Maximum Likelihood

Test for Differential Exon Usage

Estimate Common, Trended and Tagwise Negative Binomial dispersions by weighted likelihood empirical Bayes

estimateGLMRobustDisp

Empirical Robust Bayes Tagwise Dispersions for Negative Binomial GLMs using Observation Weights

estimateGLMTagwiseDisp

Empirical Bayes Tagwise Dispersions for Negative Binomial GLMs

Quasi-likelihood methods with empirical Bayes shrinkage

Gene Ontology Analysis of Differentially Expressed Genes

Plot the quasi-likelihood dispersion

Plots log-Fold Change versus log-Concentration (or, M versus A) for Count Data

Read and Merge a Set of Files Containing DGE Data

Rotation Gene Set Tests for Digital Gene Expression Data

calcNormFactors

Calculate Normalization Factors to Align Columns of a Count Matrix

Exact Binomial Tests for Comparing Two Digital Libraries

Digital Gene Expression data - class

DGEList Constructor

dispCoxReidSplineTrend

Estimate Dispersion Trend for Negative Binomial GLMs

Empirical analysis of digital gene expression data in R

estimateExonGenewiseDisp

Estimate Genewise Dispersions from Exon-Level Count Data

estimateGLMCommonDisp

Estimate Common Dispersion for Negative Binomial GLMs

maximizeInterpolant

Maximize a function given a table of values by spline interpolation.

Create a Plot of Exon Usage from Exon-Level Count Data

maximizeQuadratic

Maximize a function given a table of values by quadratic interpolation.

processAmplicons

Process raw data from pooled genetic sequencing screens

plotMDS.DGEList

Multidimensional scaling plot of distances between digital gene expression profiles

Quantile to Quantile Mapping between Negative-Binomial Distributions

systematicSubset

Take a systematic subset of indices.

Binomial or Multinomial Thinning of Counts

Predictive log-fold changes

Testing for Differential Expression Relative to a Threshold

Check for Valid DGEList object

condLogLikDerSize

Conditional Log-Likelihood of the Dispersion for a Single Group of Replicate Libraries

Competitive Gene Set Test for Digital Gene Expression Data Accounting for Inter-gene Correlation

commonCondLogLikDerDelta

Conditional Log-Likelihoods in Terms of Delta

Estimate Dispersion Trend by Binning for NB GLMs

Retrieve the Dimension Names of a DGE Object

Identify Genes with Splice Variants

splitIntoGroups

Split the Counts or Pseudocounts from a DGEList Object According To Group

Z-score Equivalents of Negative Binomial Deviate

Counts per Million or Reads per Kilobase per Million

Cut numeric vector into non-empty intervals

estimateTagwiseDisp

Estimate Empirical Bayes Tagwise Dispersion Values

Multiple Testing Across Genes and Contrasts

estimateGLMTrendedDisp

Estimate Trended Dispersion for Negative Binomial GLMs

Goodness of Fit Tests for Multiple GLM Fits

Good-Turing Frequency Estimation

movingAverageByCol

Moving Average Smoother of Matrix Columns

Negative Binomial Deviance

Top table of differentially spliced genes or exons

Table of the Top Differentially Expressed Tags

Turn a DGEList Object into a Matrix

Average Log Counts Per Million

Digital Gene Expression Likelihood Ratio Test data and results - class

Visualize the mean-variance relationship in DGE data using standardized residuals

Estimate Common Dispersion for Negative Binomial GLMs

dispCoxReidInterpolateTagwise

Estimate Tagwise Dispersion for Negative Binomial GLMs by Cox-Reid Adjusted Profile Likelihood

Extract Specified Component of a DGEList Object

Get a Recommended Value for Prior N from DGEList Object

Genewise Negative Binomial Generalized Linear Models

normalizeChIPtoInput

Normalize ChIP-Seq Read Counts to Input and Test for Enrichment

Plot Biological Coefficient of Variation

Subset DGEList, DGEGLM, DGEExact and DGELRT Objects

Sum Over Replicate Samples

weightedCondLogLikDerDelta

Weighted Conditional Log-Likelihood in Terms of Delta

Calculate Weighted Likelihood Empirical Bayes Estimates