Bad samples: in general, I believe most people would recommend removing bad
samples prior to normalization and analysis.  You don't have to rebuild the
RGChannelSet, but you do
  RGset2 = RGset[, goodSamples]

I would not exclude probes with low detection p-values.

Many people remove sex chromosomes prior to analysis and that makes some
sense.  For ease of use, I would do it after normalization; although it
might depend on the exact normalization strategy I use.  For
minfi::preprocessQuantile we treat the sex chromosomes in a special
fashion, but they don't do it for SWAN.

Best,
Kasper


On Tue, Dec 10, 2013 at 2:45 PM, Qin [guest] <guest@bioconductor.org> wrote:

>
> Hi there,
>
> I am learning minfi using a dataset containing 24 samples. I know there
> are 2 QC samples, 2 duplicated samples, and one bad sample I determined by
> minfi. My question is: what is the proper procedure to remove these samples
> from the data? Should I remove these sample file names from the sample
> sheet, and re-build the RGSet again? Similar question goes to probes
> identified to have detection p-values higher than 0.01, and CpGs in
> Chromosome X & Y. I think these CpGs should be excluded before doing
> normalization and SWAN, but I really don’t know how. One thing I have tried
> is to remove those probes (and also the 5 samples I want to remove) from
> MSet.raw, and then use this reduced MSet.raw.reduced to do SWAN:
>
> MSet.swan<-preprocessSWAN(RGSet, mSet= MSet.raw.reduced)
>
> Here RGSet is still the original one with 24 samples and all 485512 probs,
> but MSet.raw.reduced has only 19 samples and about 470K CpGs. The MSet.swan
> I got has same dimensions as MSet.raw.reduced, but I don’t know if this
> method is valid or not. I do know this cannot be applied to get MSet.norm.
>  If this is not a valid method, what is the correct way to do it?
>
> I really appreciate your help and wish you a happy holiday season!
>
> Qin
>
>  -- output of sessionInfo():
>
> R version 2.15.2 (2012-10-26)
> Platform: x86_64-redhat-linux-gnu (64-bit)
>
> locale:
>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
>  [7] LC_PAPER=C                 LC_NAME=C
>  [9] LC_ADDRESS=C               LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
>
> --
> Sent via the guest posting facility at bioconductor.org.
>

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