Hi Everyone,
I'm new to Bioconductor and also microarrays. Currently I'm working on
Illumina Human Methylation 450k data. I have done the color
adjustments and ssn normalization. Now I need to remove the probes
failing a detection p value cut-off. Would be great if someone could
tell me the best way to do this.
Thanks,
Hajja
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Hi Hajja,
On 6/22/2011 7:13 AM, khadeeja ismail wrote:
> Hi Everyone,
>
> I'm new to Bioconductor and also microarrays. Currently I'm working
> on Illumina Human Methylation 450k data. I have done the color
> adjustments and ssn normalization. Now I need to remove the probes
> failing a detection p value cut-off. Would be great if someone could
> tell me the best way to do this.
The only 'detection p value' that I know of is based on a comparison
between the PM and MM probes on an Affy 3' biased chip. Which isn't
what
you have. So I don't know that there is such a thing for you.
In addition, depending on how your analysis will proceed, you might
not
really want to do much filtering at the outset. For instance, if you
are
planning to use limma to do your comparisons, you want to keep all but
the most aberrant probes when fitting the model. This is because you
are
using all data to estimate the expected variance of a probe, so if you
filter first you may well be biasing this estimate, which is not
ideal.
Best,
Jim
>
> Thanks, Hajja
>
>
>
> [[alternative HTML version deleted]]
>
>
>
>
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James W. MacDonald, M.S.
Biostatistician
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University of Michigan
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is.na(exprs(yourMethyLumiM)[ which(detection(yourMethyLumiM)>0.01,
arr.ind=T) ]) = TRUE
assuming you use a 0.01 cutoff, that is.
On Wed, Jun 22, 2011 at 4:13 AM, khadeeja ismail <hajjja@yahoo.com>
wrote:
> Hi Everyone,
>
> I'm new to Bioconductor and also microarrays. Currently I'm working
on
> Illumina Human Methylation 450k data. I have done the color
adjustments and
> ssn normalization. Now I need to remove the probes failing a
detection p
> value cut-off. Would be great if someone could tell me the best way
to do
> this.
>
> Thanks,
> Hajja
>
>
>
> [[alternative HTML version deleted]]
>
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
>
--
If people do not believe that mathematics is simple, it is only
because they
do not realize how complicated life is.
John von Neumann<http: www-groups.dcs.st-="" and.ac.uk="" ~history="" biographies="" von_neumann.html="">
[[alternative HTML version deleted]]
Tim Triche, Jr. <tim.triche at="" ...=""> writes:
>
> is.na(exprs(yourMethyLumiM)[ which(detection(yourMethyLumiM)>0.01,
> arr.ind=T) ]) = TRUE
>
> assuming you use a 0.01 cutoff, that is.
Thanks Tim,
Will try that.
Hajja
Tim Triche, Jr. <tim.triche at="" ...=""> writes:
>
> is.na(exprs(yourMethyLumiM)[ which(detection(yourMethyLumiM)>0.01,
> arr.ind=T) ]) = TRUE
>
Thanks, Tim and James, for the tips.
Just one quick question. When and for what do we actually use the
detectionCall
function?
Hajja
Probably the same thing as I wrote. detectionCall is a 'lumi' thing,
though. (not that there's anything wrong with that) I use methylumi
for
most of what I'm doing. Not because one is better than the other, I'm
just
working on raw data instead of GenomeStudio results. So I am more
familiar
with the functions in methylumi.
On Fri, Jun 24, 2011 at 4:46 AM, Hajja <hajjja@yahoo.com> wrote:
> Tim Triche, Jr. <tim.triche@...> writes:
>
> >
> > is.na(exprs(yourMethyLumiM)[ which(detection(yourMethyLumiM)>0.01,
> > arr.ind=T) ]) = TRUE
> >
>
> Thanks, Tim and James, for the tips.
> Just one quick question. When and for what do we actually use the
> detectionCall
> function?
>
> Hajja
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
--
If people do not believe that mathematics is simple, it is only
because they
do not realize how complicated life is.
John von Neumann<http: www-groups.dcs.st-="" and.ac.uk="" ~history="" biographies="" von_neumann.html="">
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