[BioC] analysis of reference design with even dye-swap across biological replicates

Aubin-Horth Nadia Nadia.Aubin-Horth at bio.ulaval.ca
Mon Jun 20 20:31:26 CEST 2011

Hi everybody,

I am planning to analyse a microarray experiment (Agilent, 2 colors)  
and I would like to make sure I can include dye effect with the hyb  
design used.

I have 4 groups: a control group ("wild type") and 3 treatments. We  
are interested by the effect of each treatment on gene expression  
compared to the control. My plan is to maximize the statistical power  
to find differences between the control and each treatment by using a  
reference design and having the control in each hyb. Of course, I  
loose statistical power to find differences between treatments.

I have 8 biological replicates (fish) per group available.

I am interested to know if I can correctly take dye-bias into account  
using LIMMA and the following design. I am not interested in  
individual gene expression level, only mean and variance for each  

The 24 hybs are performed using the control group (all 8 individuals  
pooled) as the reference and the 8 individuals from each of the 3  
treatments used in only one hyb (no technical replicate). For each  
treatment, 4 biological replicates would be labelled in cye 3 and 4  
biological replicates would be labelled in cy5 (assigned at random  
within treatment). I would thus get an even design in terms of dye  
labelling for the reference and the treatments, but no dye swap/ 
technical replicate for a specific fish. The goal is to capture as  
much biological variance here (8 fish instead of 4 fish with dye swap)  
for the 24 hybs we can do.

The target file would look like this (T1, T2 and T3 are treatments and  
the following number represents a biological replicate)
HYB	CY3		Cy5
1		ref		T1.1
2		ref		T1.2
3		ref		T1.3
4		ref		T1.4
5		T1.5		ref
6		T1.6		ref
7		T1.7		ref
8		T1.8		ref
9		ref		T2.1
10		ref		T2.2
11		ref		T2.3
12		ref		T2.4
13		T2.5		ref
14		T2.6		ref
15		T2.7		ref
16		T2.8		ref
17		ref		T3.1
18		ref		T3.2
19		ref		T3.3
20		ref		T3.4
21		T3.5		ref
22		T3.6		ref
23		T3.7		ref
24		T3.8		ref

The comparison of interest is the average difference between the  
control and a given treatment , including dye effects

I thought I could then use the example as in section 7.3 of limma user  
guide on common reference design but including multiple biological  
replicates and a dye effect (from section 8.2)

Here the contrast matrix is made for treatment 1, T1

design <- modelMatrix(targets, ref = "ref")
design <- cbind(Dye = 1, design)
fit <- lmFit(MA, design)
cont.matrix <- makeContrasts((T1.1+T1.2+T1.3+T1.4+T1.5+T1.6+T1.7+T1.8)/ 
8, levels = design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)
topTable(fit2, adjust = "BH")

Could someone please tell me if
1) the contrast is appropriate?
2) it will be possible to estimate the dye effect as presented in the  
manual with my own hybridization design?

The hybs have not been performed yet but I assume that one can still  
tell if the design is balanced. I could use a loop design as is  
normally used in our lab but as I simply want to know what is the  
effect of each treatment, I though a reference design was appropriate,  
especially with such a large number of biological replicates.

Thank you!

Nadia Aubin-Horth
Assistant professor
Biology Department
Institute of Integrative and Systems Biology
Room 1241, Charles-Eugène-Marchand Building
1030, Ave. de la Médecine
Laval University
Quebec City (QC) G1V 0A6

Phone: 418.656.3316
Fax: 418.656.7176

web page: http://wikiaubinhorth.ibis.ulaval.ca/Main_Page

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