DRWPClass-GM-package: The DRW-GM method for disease classification

Description Details Author(s) References Examples

Description

DRWPClass-GM performs pathway-based classifier construction and precise disease status prediction by joint analysis of genomic and metabolomic data and pathway topology.

Details

Package: DRWPClassGM
Type: Package
Version: 1.0
Date: 2015-02-11
License: GPL-2

Very simple to use.
Use fit.DRWPClassGM to train the classifier.
Use predict.DRWPClassGM to predict the status of new samples.

Author(s)

Wei Liu, and Chunquan Li

References

Liu, W., et al., Topologically inferring risk-active pathways toward precise cancer classification by directed random walk. Bioinformatics, 2013. 29(17): p. 2169-77.

Examples

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	data(GProf8511)
	data(GProf3325)
	data(MProf)
	data(pathSet)
	data(dGMGraph)
	fit <- fit.DRWPClassGM(xG=GProf8511$mRNA_matrix, yG.class1=GProf8511$normal, yG.class2=GProf8511$PCA,
	xM=MProf$Meta_matrix, yM.class1=MProf$normal, yM.class2=MProf$PCA, DEBUG=TRUE, pathSet=pathSet, 
	globalGraph=dGMGraph, testStatistic="t-test", classifier = "Logistic")
	predict.DRWPClassGM(object=fit, newx=GProf3325$mRNA_matrix[,c(GProf3325$normal,GProf3325$PCA)],	
	type = "class")
	evaluate.DRWPClassGM(object=fit, newx=GProf3325$mRNA_matrix, newy.class1=GProf3325$normal,
	newy.class2=GProf3325$PCA)

cuihaibo1/drwPSurv_1.0.tar documentation built on May 12, 2017, 2:21 p.m.