[BioC] Paired two-color design
January Weiner
january.weiner at gmail.com
Tue Aug 28 08:17:39 CEST 2012
Hello,
I have a problem with the design for an experiment that I'm evaluating.
There are two parts to that problem.
The first part: we have two groups (A and B) after treatment, each in
three replicate, and two-color arrays have been created, with a
dye-swap for each replicate:
Cy3 Cy5
A1 B1
B1 A1
A2 B2
B2 A2
A3 B3
B3 A3
Here is how I'm doing it currently, but I think that this might not be
the optimal solution:
design <- cbind( ex1 = c( -1, 1, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0 ), ex2
= c( 0, 0, 0, 0, -1, 1, 1, -1, 0, 0, 0, 0 ), ex3 = c( 0, 0, 0, 0, 0,
0, 0, 0, -1, 1, 1, -1 ) )
corfit <- intraspotCorrelation( rg, design ) # rg contains the normalized arrays
fit <- lmscFit( rg, design, correlation= corfit$consensus.correlation )
cmtx <- makeContrasts( "(ex1 + ex2 + ex3)/3", levels= design )
fit <- contrasts.fit( fit, cmtx )
fit <- eBayes( fit )
Is this correct? Do I have to use intraspotCorrelation to detach the
arrays? I think this should work somehow directly, but I can't figure
out how.
The second problem is this: we have the same setup as above, except
that there are controls for A and B (before treatment). I call them
ctrlA and ctrlB, respectively. There is only one biological replicate
with a dye swap for each of these controls. The setup looks now like
that:
targets:
Cy3 Cy5
ctrlA ctrlB
ctrlB ctrlA
A1 B1
B1 A1
A2 B2
B2 A2
A3 B3
B3 A3
I want to look for interaction between the treatment effect and the
group, in other words I want the difference between (A vs controlA) -
(B vs controlB).
I use more or less the same approach as above (using intraspotCorrelation):
t2 <- targetsA2C( t )
design <- model.matrix( ~ 0 + t$group )
colnames( design ) <- levels( t$group )
# colnames( design ) are: ctrlA, ctrlB, A1, A2, A3, B1, B2, B3
corfit <- intraSpotCorrelation( rg, design )
fit <- lmsciFit( rg, design, correlation= corfit$consensus.correlation )
cmtx <- makeContrasts( "(( A1 + A2 + A3 )/3 - ctrlA) - ( B1 + B2 + B3
)/3 - ctrlB))", levels= design )
fit <- contrasts.fit( fit, cmtx )
fit <- eBayes( fit )
Is that correct?
Kind regards,
J.
--
-------- Dr. January Weiner 3 --------------------------------------
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