[BioC] methylumi: Quality Control

[Jinyan Huang]

Hi list,

I used methylumi to analysis my Illumina GoldenGate methylation data.

The data are for two disease status, I want to find the different
methylation genes in the two disease status. All sample are done in
two array.

I used qcplot find that hybridization controls failed for lots of
samples. signi cantly poorer quality are removed. When I set toKeep <-
(avgPval < 0.05), there are 133 samples remained.

If I set toKeep <- (avgPval < 0.005), there are 69 samples remained.

After I used limma to find the different  methylated genes. But for
different avgPval cutoff value, the genes I found is very different.
So which one should I trust?

Any comments?

Thanks.