Hi, we did an RNA seq experiment recently. It was 3 replicates for 2 conditions. One replicate turned out to be contaminated so I have eliminated it. I want to do differential expression analysis.

I have a script for EdgeR and it works fine, however I am getting way too many up-regulated genes. When I do a summary EdgeR tells me there are 83 up-regulated genes, 13 down-regulated. This does not really make sense and there is nothing about either of these two conditions that should cause a large activation / deactivation of transcription. I'm wondering what I can do to correct this. How do I go about diagnosing if there's anything wrong with my replicates and what can be done to correct for it.

I think the dispersion was a little high Disp = 0.10443 , BCV = 0.3232. Ive tried fiddling with the counts per million cutoff and it helps a bit but I'm wondering if I can do anything else

targets <- readTargets()
x <- read.delim("EdgeR.counts.m.txt", row.names=1, stringsAsFactors=FALSE)
y <- DGEList(counts=x[,1:5], group=targets$Treatment)
colnames(y) <- targets$Label
keep <- rowSums(cpm(y)>5) >= 3
y <- y[keep,]
dim(y)
y$samples$lib.size <- colSums(y$counts)
y <- calcNormFactors(y)
y$samples
plotMDS(y)
y <- estimateCommonDisp(y, verbose=TRUE)
y <- estimateTagwiseDisp(y)
plotBCV(y)
wm <- exactTest(y, pair=c("wt","mt"))
summary(de <- decideTestsDGE(wm))
top <- topTags(wm)
top