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