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 [[alternative HTML version deleted]]