aCGH.test {aCGH}  R Documentation 
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", subset = NULL, strt = NULL, ...)
aCGH.obj 
aCGH object containing clones' log2 ratios. 
rsp 
Response variable which is either Surv
object from survival package or continous outcome. 
test 
Currently only three values are allowed  "coxph",
"survdiff", and "linear.regression", which test for association
using Cox proportional hazards model, G^rho family of tests
(survdiff ) or linear model.

p.adjust.method 
This is a parameter controlling how the
pvalues from the univariate tests are going to be adjusted for
multiple testing. Default value is Benjamini & Hochberg (1995) FDR
method. Please refer to p.adjust function for more
help. 
subset 
Specifies subset index of clones to be tested. 
strt 
Aptional strata variable for splitting the data in different strata. 
... 
Optional parameters passed further along to each of the univariate testing functions. 
A data frame similar to the result returned from
mt.maxT
function from multtest
package with
components:
index 
Vector of row indices, between 1 and nrow(X) , where rows are
sorted first according to their adjusted pvalues, next their
unadjusted pvalues, and finally their test statistics.

teststat 
Vector of test statistics, ordered according to index . To get
the test statistics in the original data order, use
teststat[order(index)] .

rawp 
Vector of raw (unadjusted) pvalues, ordered according to
index .

adjp 
Vector of adjusted pvalues, ordered according to
index .

Peter Dimitrov
aCGH
, Surv
, mt.maxT
,
coxph
, survdiff
, p.adjust