Question: Design Matrix Microarray data analysis
0
jeevan92ultimate20 wrote:

Hi,

I'm analyzing a microarray data and stuck at the design matrix command.

I have few samples, in which I divided them into two groups i.e. "Controls" & "Diseased".

I assigned the samples information as a factor with two levels "C" & "D".

In what exact order should I assign the levels? If I assign levels as C, D then I get the logFC value as say X and if I do it as D, C I get the logFC value as -X.

Should I start with the diseased group (D) or control group (C)?

In default, in what exact order the design matrix take the levels?

My code is as follows:

info\$Group<-factor(info\$Group, levels=c("C","D"))

# ^^^ Which one should I consider first in the above command? The diseased group or control group? ^^^

levels(info\$Group)

lev<-levels(info\$Group)

design<-model.matrix(~0+info\$Group)
colnames(design)<-lev
dim(design)
head(design)
fit<-lmFit(exp, design)
names(fit)
contr.str <- c()
len<-length(lev)
for(i in 1:(len-1))contr.str<-c(contr.str, paste(lev[(i+1):len], lev[i], sep="-"))
contr.str
contr.mat<-makeContrasts(contrasts=contr.str, levels=lev)
fit2<-contrasts.fit(fit, contr.mat)
fit2<-eBayes(fit2)
names(fit2)
top <- topTable(fit2, number=nrow(fit2), adjust.method="fdr")

Thanks in advance

ADD COMMENTlink
modified 5.1 years ago • written 5.1 years ago by jeevan92ultimate20

It doesn't matter computationally, but it makes more sense to use the control sample as your referent, so levels = c('C', 'D') is a bit more pragmatic.

ADD REPLYlink written 5.1 years ago by russhh4.6k

Thanks a lot :)

ADD REPLYlink written 5.1 years ago by jeevan92ultimate20
Please log in to add an answer.

Content
Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1669 users visited in the last hour