Dear Gordon, 

Thanks for your timely reply.

Yes, I did apply weight option,  giving zero weight to spots whose variable "flag" is less than -1. Now it makes sense to me. LogFC(2) is obtained from MA.2, and LogFC(1) is directly from topTable list.

There are 3 dye-swap pairs and 1 single array. Here are the commands:

###################################################################
 targets <- read.delim2("Data/targets.txt", row.names = NULL, na.strings = "NA")
f <- function(x) as.numeric(x$Flags > -1)

design <- c(1,-1,1,-1,1,-1,1)

RG <- read.maimages(targets,columns=list(Rf = "F635 Median", Gf="F532 Median",Rb = "B635 Median", Gb= "B532 Median"), source = "genepix", path = "Data", wt.fun=f)

spottypes <- readSpotTypes(path="Data")
RG$genes$Status <- controlStatus(spottypes, RG)

RG.2 <- RG
MA.2 <- normalizeWithinArrays(RG.2,
                              layout = RG$printer,
                              method = "printtiploess",
                              bc.method = "subtract")


cor <- duplicateCorrelation(MA.2, design, ndup=4, spacing = 1408)

fit.2 <- lmFit(MA.2, design = design, spacing = 1408, ndups=4, correlation = cor$consensus.correlation)
fit.2 <- eBayes(fit.2)
#######################################################################


--- On Fri, 10/24/08, Gordon K Smyth <smyth@wehi.EDU.AU> wrote:
From: Gordon K Smyth <smyth@wehi.EDU.AU>
Subject: LogFC in Limma
To: bioconductor@stat.math.ethz.ch

Date: Friday, October 24, 2008, 8:58 PM

Dear Kevin,

After sending my previous reply, I re-read your email and realized your
question is probably about a coefficient from lmFit() rather than a question
about your probe replicates.

It is impossible to give you a definite answer because you haven't told us
what what your design is or what logFC(1) is measuring, what model you're
fitting, whether you used contrasts.fit and so on.  Ordinarily, people will give
enough code to make these things clear.

Since you appear to have at least three columns in your design matrix, it seems
rather unlikely that logFC(1) could be a simple average of all the arrays.

Also, do you have quality weights in your data or blocks in your fit?  In these
cases, limma will compute weighted averages, which are not the same as ordinary
averages.

Best wishes
Gordon

> Date: Thu, 23 Oct 2008 13:25:46 -0700 (PDT)

> Subject: [BioC] LogFC in Limma
> To: bioconductor@stat.math.ethz.ch
> Message-ID: <696005.24645.qm@web32404.mail.mud.yahoo.com>
> Content-Type: text/plain
> 
> Hello lists,
> 
> I am using Bioconductor/Limma package to analyze microRNA arrays.
> I have 7 replicate two-color arrays, 4 probe replicates each array. Follow
Limma procedures, I had a list from topTable with LogFC(1) and other columns. In
addition, I produced LogFC for each individual arrays from MAlist, the average
LogFC(2) were then taken from 7 arrays to compare LogFC(1).
> 
> The LogFC(2) is similar to LogFC(1), for example 3.12 vs 3.2, but
they're not exactly the same.
> 
> My question is that why aren't these two columns of value the same?
Did I calculate it mistakenly or something behind this during the Limma
procedures?
> 
> Could anyone kindly explain it?
> 
> Thanks.
> 
> Kevin



      
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