| designMatrix {ArrayTools} | R Documentation |
Class to Contain the Design Matrix that Used for Linear Regression
new("designMatrix", ..., target, covariates, intIndex=0)
This create as design matrix class. target is a data frame
that contains chip and covaraite information, or experimental phenotypes
recorded in eSet and ExpressionSet-derived classes. covariates is
a list of 1-n covariates. If intIndex=0, the interaction effect
is not considered; otherwise, use two integers to indicate which
covariates are considered for interaction effect. For example,
if covariates <- c("estrogen","drug","time") and you are considering
the interaction between "estrogen" and "time", then you would write
intIndex=c(1,3)
design:target:target datacovariates:covariatesintIndex:intIndexsignature(object = "designMatrix"):
access the covariates slot signature(object = "designMatrix"):
access the design slotsignature(object = "designMatrix"):
access the intIndex slotsignature(object = "designMatrix"):
access the target slotsignature(.Object = "designMatrix"):
create a new designMatrix classsignature(object = "designMatrix"):
print the designMatrix classXiwei Wu, Arthur Li
data(eSetExample)
## One-way Anova
(design1<- new("designMatrix", target=pData(eSetExample), covariates = "Treatment"))
## Randomized block design
(design2<- new("designMatrix", target=pData(eSetExample),
covariates = c("Treatment", "Group")))
## Interaction design
(design3<- new("designMatrix", target=pData(eSetExample),
covariates = c("Treatment", "Group"), intIndex=c(1,2)))