GeNetClassifierReturn-class: Class "GeNetClassifierReturn"

In geNetClassifier: Classify diseases and build associated gene networks using gene expression profiles

Description

Object wich wraps all the items returned by geNetClassifier. It usually contains the classifier, the genes ranking and information, the network and any other requested statistics.

Methods

names

signature(x = "GeNetClassifierReturn"): Shows the available slots in the object.

overview

signature(object = "GeNetClassifierReturn"): Shows an overview of all the slots in the object.

Slots

Available slots deppends on the arguments used to call geNetClassifier():

call:

call. Always available.

classifier:

list. SVM classifier. Only available if geNetClassifier() was called with option buildClassifier=TRUE (default settings).

classificationGenes:

GenesRanking. Genes used to train the classifier. Only available if geNetClassifier() was called with option buildClassifier=TRUE (default settings).

generalizationError:

GeneralizationError. Statistics calculated for the current training set and options.
Only available if geNetClassifier() was called with option estimateGError=TRUE (False by default).

genesRanking:

GenesRanking. Whole genes ranking (if returnAllGenesRanking=TRUE) or significant genes ranking (if returnAllGenesRanking=FALSE, includes only the genes with posterior probability over lpThreshold)

genesRankingType:

character. "all", "significant" or "significantNonRedundant"

genesNetwork:

List of GenesNetwork. Only available if geNetClassifier() was called with option calculateNetwork=TRUE (default settings).

genesNetworkType:

character. At the moment, only "topGenes" available.

Author(s)

Bioinformatics and Functional Genomics Group. Centro de Investigacion del Cancer (CIC-IBMCC, USAL-CSIC). Salamanca. Spain

See Also

Main package function and classifier training: geNetClassifier
plot.GeNetClassifierReturn

Examples

######
# Load data and train a classifier
######

# Load an expressionSet:
library(leukemiasEset)
data(leukemiasEset)

# Select the train samples: 
trainSamples<- c(1:10, 13:22, 25:34, 37:46, 49:58) 
# summary(leukemiasEset$LeukemiaType[trainSamples])

# Train a classifier or load a trained one:
# leukemiasClassifier <- geNetClassifier(leukemiasEset[,trainSamples], 
#    sampleLabels="LeukemiaType", plotsName="leukemiasClassifier") 
data(leukemiasClassifier) # Sample trained classifier

######
# Explore the returned object
######
# Global view of the object and its structure:
leukemiasClassifier
names(leukemiasClassifier)

### Depending on the available slots:
# Call and acess to the classifier:
leukemiasClassifier@call
leukemiasClassifier@classifier

# Genes used for training the classifier:
numGenes(leukemiasClassifier@classificationGenes)
leukemiasClassifier@classificationGenes
# Show de tetails of the genes of a class
genesDetails(leukemiasClassifier@classificationGenes)$AML 
# If your R console wraps the table rows, try widening your display width: 
# options(width=200)

# Generalization Error estimated by cross-validation:
leukemiasClassifier@generalizationError
overview(leukemiasClassifier@generalizationError)
# i.e. probabilityMatrix:
leukemiasClassifier@generalizationError@probMatrix
# i.e. statistics of the genes chosen in any of the CV loops for for AML:
leukemiasClassifier@[e-mail]$AML
	
# List of Networks by classes:
leukemiasClassifier@genesNetwork
# Access to the nodes or edges of each network:
	getEdges(leukemiasClassifier@genesNetwork$AML)
	getNodes(leukemiasClassifier@genesNetwork$AML)	
		
# Genes ranking:
leukemiasClassifier@genesRanking
	# Number of available genes in the ranking:
	numGenes(leukemiasClassifier@genesRanking)
	# Number of significant genes 
	# (genes with posterior probability over lpThreshold, default=0.95)
	numSignificantGenes(leukemiasClassifier@genesRanking)		
	# Top 10 genes of CML:
	genesDetails(leukemiasClassifier@genesRanking)$CML[1:10,]
	# To get a sub ranking with the top 10 genes:
	getTopRanking(leukemiasClassifier@genesRanking, 10)
	# Genes details of the top 10 genes:
	genesDetails(getTopRanking(leukemiasClassifier@genesRanking, 10))

geNetClassifier documentation built on Nov. 8, 2020, 4:53 p.m.