Entering edit mode
On the advice of this post, I tried the preprocessNoob()
-> preprocessQuantile()
route of normalisation in the minfi package. Using the resulting object from preprocessNoob
, when I run preprocessQuantile
I get the error:
Error in if ((is(object, "MethylSet") || is(object, "GenomicMethylSet")) && : missing value where TRUE/FALSE needed
Which was odd. Checking the code for preprocessQuantile
, we can see that it runs this line:
if ((is(object, "MethylSet") || is(object, "GenomicMethylSet")) && preprocessMethod(object)["rg.norm"] != "Raw (no normalization or bg correction)") warning("preprocessQuantile has only been tested with 'preprocessRaw'")
Which looks for the preprocess method, and the rg.norm
column. Which doesn't exist. Running the code:
preprocessMethod(lumi.norm.bgcorr)
Gives the result:
mu.norm "Noob, dyeCorr=TRUE"
...and mu.norm != rg.norm - Any advice?
Thanks Kasper. So while
preprocessFunnorm
andpreprocessIllumina
both have implementations for background correction prior to the normalisation, I know thatpreprocessQuantile
andpreprocessSWAN
don't. If I remember right,preprocessFunnorm
is an extension of the quantile method, so would it not make sense to background and dye bias correct prior to normalisation? (I realise it isn't tested, but I just wanted to be sure my logic was sound)Cheers Kasper - I will do some testing between
preprocessQuantile
andpreprocessNoob
+preprocessQuantile
, once the bug is sorted out!Hi Andrew,
I am trying to apply some normalization method on EPIC array and came to this topic. As you discussed above what is your opinion about applying preprocessQuantile and preprocessNoob + preprocessQuantile? Which method worked better for your data normalization?
Thanks.