modelOutcome {MergeMaid} | R Documentation |
Given a set of merged studies, this function calculates study specific regression coefficients for each gene.
modelOutcome(x,outcome,outcome2=NULL,method=c("linear","logistic","cox"),...)
x |
Object of class mergeExprSet. |
method |
Method specifies the model used to generate coefficients. At this time only linear regression, logistic regression, and Cox hazard rates are implemented. |
outcome, outcome2 |
The format for the outcome variable depends on the model used. For linear regression, outcome should be a continous response variable, for logistic regression, it should be a binary response variable, and for Cox hazard rates it should be time of event. Outcome 2 is currently used only in the calculation of hazard rates, and should be a binary variable indicating censoring status for each subject. If outcome is a vector of length equal to number of studies, then each element represents the column in the exprSet phenoData slot for that study. If outcome is a list, then each list element should have actual outcome data for the corresponding study. |
... |
Not implemented at this time |
The output is a mergeCoeff object.
modelOutcome
, mergeCoeff-class
data(mergeData) merged <- mergeExprs(sample1,sample2,sample3) log.coeff <- modelOutcome(merged,outcome=c(1,1,1),method="logistic") plot(coeff(log.coeff)) linear.coeff <- modelOutcome(merged[1:2],outcome=c(3,3),method="linear") plot(zscore(linear.coeff),xlab="study 1",ylab="study 2") event1<-rbinom(100,1,.5) event2<-rbinom(50,1,.5) event3<-rbinom(70,1,.5) out1<-rnorm(100,5,1) out2<-rnorm(50,5,1) out3<-rnorm(70,5,1) out<-list(out1,out2,out3) even<-list(event1,event2,event3) cox.coeff<-modelOutcome(merged,outcome2=even,outcome=out,method="cox") plot(coeff(cox.coeff))