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Sally
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@sally-2430
Last seen 10.2 years ago
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=TRU
E,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
