Extraction of Differential Gene Expression


[Up] [Top]

Documentation for package ‘edge’ version 2.30.0

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