[BioC] Interpreting topTable results for limma factorial design

[Sally]

I have a 2x2 factorial design which I ran through limma.  The factors are (1) species  [(Coho (c)) and Sockeye (s))] and (2) sample time (0, 24, 48 and 96 hours).

 

The R script used was:

 

source("http://bioconductor.org/biocLite.R")

library(limma)

library(Biobase)

exprdata<-read.table("exprsData.txt", header=TRUE,sep="\t",row.names=1,as.is=TRUE,fill=TRUE,)

phenotypicdata<-read.table("phenotypicdata.txt",row.names=1,header=TRUE,sep="\t")

myexprdata<-as.matrix(exprdata)

myphenotypicdata<-as.data.frame(phenotypicdata)

adf<-new("AnnotatedDataFrame",data=phenotypicdata)

eset<-new("ExpressionSet",exprs=myexprdata,phenoData=adf)

targets <- readTargets("targets.txt")

TS <- paste(targets$Species, targets$Time, sep=".")

TS <- factor(TS)

design <- model.matrix(~0+TS)

colnames(design) <- levels(TS)

fit <- lmFit(eset, design)

cont.matrix<-makeContrasts(s0vss24=s.0-s.24, s24vss48=s.24-s.48, s48vss96=s.48-s.96, c0vsc24=c.0-c.24, c24vsc48=c.24-c.48, c48vsc96=c.48-c.96, s0vsc0=s.0-c.0, s24vsc24=s.24-c.24, s48vsc48=s.48-c.48, s96vsc96=s.96-c.96, levels=design)

fit2 <- contrasts.fit(fit, cont.matrix)

fit2 <- eBayes(fit2)

c48vsc96<-topTable(fit2,coef="c48vsc96",number=400,adjust.method="BH",p.value=1)

 

I have appended an Excel file which includes both the topTable results and the average M values for both coho 48 hours and coho 96 hours for those genes with a p value less than 0.05.

 

My questions are:

 

For gene #1, what does the logFC mean?  

At which sample time (48 or 96 hours) is this gene down-regulated -2.67 (fold change)?

The logFC does not appear to correlate with either of the two M values (48hrs = +0.63, 96 hrs = +2.42)?

Something seems wrong to me.

 

Thanks 

 

Sally Goldes