Package DRWPClassGM implements the DRW-GM method. DRW-GM is a pathway-based classification method which performs classifier construction and precise disease status prediction by joint analysis of genomic and metabolomic data and pathway topology. How to use DRWPClassGM Essential dependence platform To run DRWPClassGM, you should make sure that your computer has installed Weka. The Weka downloaded website (in our analysis we installed weka-3-7-12jre.exe):

The available resource of DRWPClass can be downloaded as follows: Package source: DRWPClassGM_1.0.tar.gz

Windows binary:

Reference manual: DRWPClassGM-manual.pdf

Dependent packages: Depends: R (>= 3.1.1), igraph, Matrix, RWeka, samr

#####Example code for predicting disease class


load example data

data(GProf8511) data(GProf3325) data(MProf) data(pathSet) data(dGMGraph)

train a classifier

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 classification performance

evaluate.DRWPClassGM(object=fit, newx=GProf3325$mRNA_matrix, newy.class1=GProf3325$normal, newy.class2=GProf3325$PCA)

cuihaibo1/123 documentation built on May 12, 2017, 2:20 p.m.