aCGH.test function tests for association of each clone in an
  univariate manner with censored or continous outcome by fitting Cox
  proportional hazards model or linear regression model. There is also
  an alternative to Cox prop. hazards - testing for differences in
  survival curves defined by the groups in the outcome variable using
  the $G^\rho$ family of tests.
aCGH.test(aCGH.obj, rsp, test = c("survdiff","coxph", "linear.regression"), p.adjust.method = "fdr",imputed=TRUE,  subset = NULL, strt = NULL, ...)Surv
    object from survival package or continous outcome.survdiff) or linear model.
  p.adjust function for more
    help.mt.maxT function from multtest package with
  components:
  nrow(X), where rows are
    sorted first according to their adjusted $p$-values, next their
    unadjusted $p$-values, and finally their test statistics.
  index. To get
    the test statistics in the original data order, use
    teststat[order(index)].
  index.
  index.
  aCGH, Surv, mt.maxT,
  coxph, survdiff, p.adjust