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edge (version 2.4.2)

Extraction of Differential Gene Expression

Description

The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as snm, sva, and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.

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Version

Version

2.4.2

License

MIT + file LICENSE

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Repository

https://github.com/jdstorey/edge

Maintainer

Last Published

February 15th, 2017

Functions in edge (2.4.2)

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

maximizeQuadratic

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

Formulates the experimental models

Gene expression dataset from Calvano et al. (2005) Nature

Gene expression dataset from Idaghdour et al. (2008)

commonCondLogLikDerDelta

Conditional Log-Likelihoods in Terms of Delta

DGEList Constructor

estimateCommonDisp

Estimate Common Negative Binomial Dispersion by Conditional Maximum Likelihood

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

Negative Binomial Deviance

Rotation Gene Set Tests for Digital Gene Expression Data

Quantile to Quantile Mapping between Negative-Binomial Distributions

Create a deSet object from an ExpressionSet

differential expression of Digital Gene Expression data - class

Digital Gene Expression Likelihood Ratio Test data and results - class

estimateGLMRobustDisp

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

Digital Gene Expression data - class

estimateTrendedDisp

Estimate Empirical Bayes Trended Dispersion Values

Locally Weighted Mean By Column

maximizeInterpolant

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

Predictive log-fold changes

Summary of deFit and deSet

Fitted data from the full model

calcNormFactors

Calculate Normalization Factors to Align Columns of a Count Matrix

dispCoxReidInterpolateTagwise

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

dropEmptyLevels

Drop Levels of a Factor that Never Occur

Genewise Negative Binomial Generalized Linear Models

Test for Differential Expression Relative to a Threshold

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

Extraction of Differential Gene Expression

Regression coefficients from full model fit

Calculate Weighted Likelihood Empirical Bayes Estimates

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

estimateGLMCommonDisp

Estimate Common Dispersion for Negative Binomial GLMs

Generate a deSet object with full and null models

Get a Recommended Value for Prior N from DGEList Object

Linear regression of the null and full models

Gene expression dataset from Rodwell et al. (2004)

Residuals of null model fit

Gini dispersion index

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

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

estimateGLMTrendedDisp

Estimate Trended Dispersion for Negative Binomial GLMs

Genewise Negative Binomial Generalized Linear Models with Quasi-likelihood Tests

Plot the quasi-likelihood dispersion

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

Check for Valid DGEList object

Estimate the q-values for a given set of p-values

Full model equation

Top table of differentially spliced genes or exons

Fitted data from the null model

Modular optimal discovery procedure (mODP)

Statistic type used in analysis

Average Log Counts Per Million

Estimate Common Dispersion for Negative Binomial GLMs

Empirical analysis of digital gene expression data in R

Goodness of Fit Tests for Multiple GLM Fits

Binomial or Multinomial Thinning of Counts

splitIntoGroups

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

The differential expression class for the model fits

Performs F-test (likelihood ratio test using Normal likelihood)

Show function for deFit and deSet

Null model equation from deSet object

Estimate Dispersion Trend by Binning for NB GLMs

equalizeLibSizes

Equalize Library Sizes by Quantile-to-Quantile Normalization

estimateGLMTagwiseDisp

Empirical Bayes Tagwise Dispersions for Negative Binomial GLMs

Turn a DGEList Object into a Matrix

estimateExonGenewiseDisp

Estimate Genewise Dispersions from Exon-Level Count Data

Gene Ontology or KEGG Analysis of Differentially Expressed Genes

plotMDS.DGEList

Multidimensional scaling plot of distances between digital gene expression profiles

Subset DGEList, DGEGLM, DGEExact and DGELRT Objects

systematicSubset

Take a systematic subset of indices.

processAmplicons

Process raw data from pooled genetic sequencing screens

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

apply_jackstraw

Non-Parametric Jackstraw for Principal Component Analysis (PCA)

Residuals of full model fit

The optimal discovery procedure

The differential expression class (deSet)

edgeRUsersGuide

View edgeR User's Guide

Extract Specified Component of a DGEList Object

Retrieve the Dimension Names of a DGE Object

Differential splicing plot

Rotation Gene Set Tests for Digital Gene Expression Data

normalizeChIPtoInput

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

Sum Over Replicate Samples

Estimate surrogate variables

dispCoxReidSplineTrend

Estimate Dispersion Trend for Negative Binomial GLMs

Counts per Million or Reads per Kilobase per Million

estimateTagwiseDisp

Estimate Empirical Bayes Tagwise Dispersion Values

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

Mean-Difference Plot of Count Data

weightedCondLogLikDerDelta

Weighted Conditional Log-Likelihood in Terms of Delta

movingAverageByCol

Moving Average Smoother of Matrix Columns

Identify Genes with Splice Variants

Z-score Equivalents of Negative Binomial Deviate

Supervised normalization of data in edge

Exact Binomial Tests for Comparing Two Digital Libraries

condLogLikDerSize

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

Cut numeric vector into non-empty intervals

adjustedProfileLik

Adjusted Profile Likelihood for the Negative Binomial Dispersion Parameter

Explore the mean-variance relationship for DGE data

Plot Biological Coefficient of Variation

Test for Differential Exon Usage

Read and Merge a Set of Files Containing Count Data

Matrix representation of null model

Good-Turing Frequency Estimation

Turn a TopTags Object into a Dataframe

Access/set qvalue slot

Table of the Top Differentially Expressed Tags

Individuals sampled in experiment

Multiple Testing Across Genes and Contrasts

Matrix representation of full model

Digital Gene Expression Generalized Linear Model results - class