[BioC] finding a very large number of false positives using edgeR

[Blum, Charles]

Hi,

I did run the same analysis using edgeR (glm), edgeR (as below) and  DESeq. All had very similar results.
Yes, I am simply testing between biological replicates with the exact same treatment only from 2 different Illumina runs.

This  simple example edgeR code also gave similar results:

> group
S180_Total_30_r1 S180_Total_30_r2 S180_Total_30_r4  S437_Total_30_1  S437_Total_30_2
            S180             S180             S180             S437             S437
 S437_Total_30_3
            S437
Levels: S180 S437

y <- DGEList(counts=A, group=group, genes=genes)
 y <- calcNormFactors(y)
y <- estimateCommonDisp(y)
y <- estimateTagwiseDisp(y)
fit <- exactTest(y)
fit$table <- cbind(fit$table, FDR=p.adjust(fit$table$PValue,method="BH"))
sum(fit$table$FDR <= 0.1) # The result is 6,674 genes

Thanks,
Charles Blum
ICNN - UCLA

On Jan 15, 2014, at 3:59 PM, Steve Lianoglou wrote:

> Steve Lianoglou


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