[BioC] topTable changes

[Sue Jones]

I have used the following code to find differentially expressed genes
: based on affymetrix data when treating cells with water (controls) and 
ethanol (treatment).

files <- c("W05h_1.CEL", "W0h_1.CEL", "W2h_1.CEL",
"W2h_2.CEL", "W4h_1.CEL",  "E2h_1.CEL",  "E2h_2.CEL",
"E2h_3.CEL", "E2h_4.CEL")
Data <- ReadAffy(filenames = files)
Data_gcrma <- gcrma(Data)
design<- cbind(WAT=c(1,1,1,1,1,0,0,0,0), ETH=c(0,0,0,0,0,1,1,1,1))
design

fit <- lmFit(Data_gcrma,design)
cont.matrix <- makeContrasts(WATvsETH=ETH-WAT, levels=design)
fit2<- contrasts.fit(fit,cont.matrix)
fit3 <- eBayes(fit2)

tab <- topTable(fit3, n=1500, adjust="fdr")
genenames <- as.character(tab$ID)
ll <- getLL(genenames, "drosgenome1")
sym <- getSYMBOL(genenames, "drosgenome1")
tab2 <- data.frame(sym,tab)

diff_exp <- tab2[tab2$P<0.05 & tab2$M<0.0,]
print("No down reg genes:"); length(diff_exp$ID)

diff_exp <- tab2[tab2$P<0.05 & tab2$M>0.0,]
print("No up reg genes:") ;length(diff_exp$ID)


The question I have is about the topTable function. Does this now only 
produce a P.value column which contains the adjusted P-values and is this 
column tagged as "P"? Are the two lines of code that extract the genes 
with P values <0.05 correct?

diff_exp <- tab2[tab2$P<0.05 & tab2$M<0.0,]
print("No down reg genes:"); length(diff_exp$ID)


previously I had code which used $adj.P.Val as a filter but this does not 
work any more.

Thanks

Sue Jones
University of Sussex