MergeMaid (version 2.44.0)

modelOutcome: Compare regression coefficients across studies

Description

Given a set of merged studies, this function calculates study specific regression coefficients for each gene.

Usage

modelOutcome(x,outcome,outcome2=NULL,method=c("linear","logistic","cox"),...)

Arguments

x

Object of class mergeExpressionSet.

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 ExpressionSet 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

Value

See Also

modelOutcome, mergeCoeff-class

Examples

  if(require(Biobase) & require(MASS) & require(survival)){
  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))

  }