Dear List:

I'm using limma package on an affy dataset. I have pre- and post- 
treatment biopsies, and some biopsies came from different regions of 
tumors and were profiled more than once, e.g. sample 01_01_Post (so they 
should be technical replicates?). There are some samples missing pre- or 
post- counterparts. The phenoData likes this:

	Subject 	Treatment 	Subject.Treat 	Pairs
1 	01_01 	Pre 	01_01_Pre 	1
2 	01_01 	Post 	01_01_Post 	1
3 	01_01 	Post 	01_01_Post 	1
4 	01_02 	Pre 	01_02_Pre 	NA
5 	02_01 	Pre 	02_01_Pre 	2
6 	02_01 	Post 	02_01_Post 	2
7 	02_02 	Pre 	02_02_Pre 	3
8 	02_02 	Post 	02_02_Post 	3
9 	02_03 	Pre 	02_03_Pre 	NA
10 	03_01 	Pre 	03_01_Pre 	4
11 	03_01 	Post 	03_01_Post 	4
12 	03_02 	Pre 	03_02_Pre 	5
13 	03_02 	Pre 	03_02_Pre 	5
14 	03_02 	Post 	03_02_Post 	5
15 	03_03 	Post 	03_03_Post 	NA
16 	03_04 	Pre 	03_04_Pre 	6
17 	03_04 	Pre 	03_04_Pre 	6
18 	03_04 	Post 	03_04_Post 	6
19 	03_05 	Pre 	03_05_Pre 	7
20 	03_05 	Post 	03_05_Post 	7

 
The purpose is to detect treatment effects with more statistical power. 
I have 2 ways of building matrix as below:
/==================================
#First possibility:
//design <- model.matrix(Treatment)
corfit <- duplicateCorrelation(data, design=design, ndups=1, block=Subject)
fit <- lmFit(data, design, block=Subject, cor=corfit$consensus)
fit <- eBayes(fit)
topTable(fit, coef=2)///
==========================================
I was trying to use block=Subject.Treat for corfit, but got an error 
message of " Too much damping -convergence tolerance not achievable in: 
glmgam.fit(.....)". I can only run with block=Subject for corfit. Can 
somebody explain this to me?
==========================================
/#Second possibility: //
phenoData.pairs <- subset(phenoData, Pairs!="NA")
data.pairs <- data[ ,row.names(phenoData.pairs)]
design <- model.matrix(~phenoData.pairs$Pairs + phenoData.pairs$Treatment)
fit <- lmFit(data.pairs, design)
fit <- eBayes(fit)
topTable(fit, coef=3)/
=========================================
The above code would ignore data from non-paired samples. Does it 
consider the technical replicates for some of the samples?

Thanks,
Xia





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