Description Usage Arguments Value Author(s) See Also Examples
Create a design matrix for a linear model
1 | make.design(target, cov, int=NULL)
|
target |
a data frame contains chip and covaraite information, or experimental phenotypes recorded in eSet and ExpressionSet-derived classes |
cov |
a list of 1-n covariates |
int |
if int=NULL, the interaction effect is not considered; otherwise, use two integers to indicate which covariates are considered for interaction effect. For example, if cov<-c("estrogen","drug","time") and you are considering the interaction between "estrogen" and "time", then you would write int=c(1,3) |
a matrix containing design matrix for the linear model
Xiwei Wu xwu@coh.org, Xuejun Arthur Li xueli@coh.org
1 2 3 4 5 6 7 8 9 10 | target<-data.frame(drug=(c(rep("A",4),rep("B",4),rep("C",4))),
gender=factor(c(rep("M",6),rep("F",6))),
group=factor(rep(c(1,2,3),4)))
#To create a design matrix using "drug", "gender" as covariates
design1<-make.design(target, c("drug","gender"))
#To create a design matrix by using "drug","gender","group" as covariates,
#and consider the interaction effect of "drug" and "group"
design2<-make.design(target, c("drug","gender", "group"), int=c(1,3))
|
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