Dear Sir/Madam,



I meet some problems when I use the limma package to analysis the Agilent
single channel microarray. I got 8 samples (with 8*60K array) results as
following:

Samples: (T1, T2, T3) =Treat1

Samples: (T4, T5, T6)=Treat2
Samples: (C1, C2)=Control
my targets.txt contain:
file_name conditon
x1.txt T1
x2.txt T2
x3.txt T3
x4.txt T4
x5.txt T5
x6.txt T6
x7.txt C1
x8.txt C8


I want to get the different expressed genes under 3 conditions: Treat1 vs
Control, Treat2 vs Control, Treat2 vs Treat1 with the following format:

*GROUP1*

*GROUP2*

*CONTROL*

*GROUP1-vs-CONTROL*

*GROUP2-vs-CONTROL*

*GROUP1-vs-GROUP2*

*Probeid*

*Accession*

*T1*

*T2*

*T3*

*T4*

*T5*

*T6*

*C1*

*C2*

*avg-group1*

*avg-group2*

*avg-control*

*FC*

*UP/DOWN*

*P value*

*FC*

*UP/DOWN*

*P value*

*FC*

*UP/DOWN*

*P value*

CUST_PI5

AB91

3

1

1

1

2

4

6

6

2

2.5

6

6

DOWN

0.01

2

DOWN

0.02

1

DOWN

0.2



My R script as follow:

library(limma)

targets <- readTargets("targets.txt")

x <- read.maimages(targets[,"file_name"], source="agilent",green.only=TRUE)

y <- backgroundCorrect(x, method="normexp")

y <- normalizeBetweenArrays(y, method="quantile")

y.ave <- avereps(y, ID=y$genes$ProbeName)

f <- factor(targets$condition, levels = unique(targets$condition))

design <- model.matrix(~0 + f)

colnames(design) <- levels(f)



fit <- lmFit(y.ave, design)

contrast.matrix <- makeContrasts("Treat1-C",
"Treat2-C","Treat2-Treat1",levels=design)

fit2 <- contrasts.fit(fit, contrast.matrix)

fit2 <- eBayes(fit2)

write.table(topTable(fit2,adjust="BH",number="44000"),
file="out_file.txt",sep="\t")



I got the results as following:

*ProbeName*

*SystematicName*

*Treat1.C*

*Treat2.C*

*Treat1.Treat2*

*AveExpr*

*F*

*P.Value*

*adj.P.Val*

CUST_248

EV478

-0.54306

-8.90559

8.362525

14.51936

2562.081

1.97E-10

6.12E-06


The problem is that I can’t get the normalized data, every group average
data, FC with up/down label in a file just like the previous format. I
write you for help and look forward to receiving your reply.

Thanks a lot.



Yong Li

Institute of Plant Physiology and Ecology, SIBS, CAS

	[[alternative HTML version deleted]]

