ArrayTools (version 1.32.0)

designMatrix: Class to Contain the Design Matrix that Used for Linear Regression

Description

Class to Contain the Design Matrix that Used for Linear Regression

Creating Objects

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)

Slots

design:

contains the design matrix

target:

contains the target data

covariates:

contains the covariates

intIndex:

contains the intIndex

Methods

getCovariates

signature(object = "designMatrix"): access the covariates slot

getDesign

signature(object = "designMatrix"): access the design slot

getIntIndex

signature(object = "designMatrix"): access the intIndex slot

getTarget

signature(object = "designMatrix"): access the target slot

initialize

signature(.Object = "designMatrix"): create a new designMatrix class

show

signature(object = "designMatrix"): print the designMatrix class

See Also

contrastMatrix

Examples

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)))