Extraction of Differential Gene Expression

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Documentation for package ‘edge’ version 2.30.0

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

Help Pages

edge-package	Extraction of Differential Gene Expression
apply_qvalue	Estimate the q-values for a given set of p-values
apply_qvalue-method	Estimate the q-values for a given set of p-values
apply_snm	Supervised normalization of data in edge
apply_snm-method	Supervised normalization of data in edge
apply_sva	Estimate surrogate variables
apply_sva-method	Estimate surrogate variables
betaCoef	Regression coefficients from full model fit
betaCoef-method	Regression coefficients from full model fit
build_models	Generate a deSet object with full and null models
build_study	Formulates the experimental models
deFit-class	The differential expression class for the model fits
deSet	Create a deSet object from an ExpressionSet
deSet-class	The differential expression class (deSet)
deSet-method	Create a deSet object from an ExpressionSet
edge	Extraction of Differential Gene Expression
endotoxin	Gene expression dataset from Calvano et al. (2005) Nature
fitFull	Fitted data from the full model
fitFull-method	Fitted data from the full model
fitNull	Fitted data from the null model
fitNull-method	Fitted data from the null model
fit_models	Linear regression of the null and full models
fit_models-method	Linear regression of the null and full models
fullMatrix	Matrix representation of full model
fullMatrix-method	Matrix representation of full model
fullMatrix<-	Matrix representation of full model
fullMatrix<--method	Matrix representation of full model
fullModel	Full model equation
fullModel-method	Full model equation
fullModel<-	Full model equation
fullModel<--method	Full model equation
gibson	Gene expression dataset from Idaghdour et al. (2008)
individual	Individuals sampled in experiment
individual-method	Individuals sampled in experiment
individual<-	Individuals sampled in experiment
individual<--method	Individuals sampled in experiment
kidney	Gene expression dataset from Rodwell et al. (2004)
kl_clust	Modular optimal discovery procedure (mODP)
kl_clust-method	Modular optimal discovery procedure (mODP)
lrt	Performs F-test (likelihood ratio test using Normal likelihood)
lrt-method	Performs F-test (likelihood ratio test using Normal likelihood)
nullMatrix	Matrix representation of null model
nullMatrix-method	Matrix representation of null model
nullMatrix<-	Matrix representation of null model
nullMatrix<--method	Matrix representation of null model
nullModel	Null model equation from deSet object
nullModel-method	Null model equation from deSet object
nullModel<-	Null model equation from deSet object
nullModel<--method	Null model equation from deSet object
odp	The optimal discovery procedure
odp-method	The optimal discovery procedure
qvalueObj	Access/set qvalue slot
qvalueObj-method	Access/set qvalue slot
qvalueObj<-	Access/set qvalue slot
qvalueObj<--method	Access/set qvalue slot
resFull	Residuals of full model fit
resFull-method	Residuals of full model fit
resNull	Residuals of null model fit
resNull-method	Residuals of null model fit
show	Show function for deFit and deSet
show-method	Show function for deFit and deSet
sType	Statistic type used in analysis
sType-method	Statistic type used in analysis
summary	Summary of deFit and deSet
summary-method	Summary of deFit and deSet