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yong li
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10
@yong-li-5846
Last seen 9.6 years ago
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 cant 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
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