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
:contains the design matrix
target
:contains the target
data
covariates
:contains the covariates
intIndex
:contains the intIndex
signature(object = "designMatrix")
:
access the covariates
slot
signature(object = "designMatrix")
:
access the design
slot
signature(object = "designMatrix")
:
access the intIndex
slot
signature(object = "designMatrix")
:
access the target
slot
signature(.Object = "designMatrix")
:
create a new designMatrix class
signature(object = "designMatrix")
:
print the designMatrix class
Xiwei 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)))