[BioC] R-2.2 and BioConductor 1.7: changes in GC-RMA and fitPLMprocedures
Groot, Philip de
philip.degroot at wur.nl
Tue Oct 18 16:27:51 CEST 2005
Hello Ben,
Quality assessment is not my only concern. I am performing subsequent
analyses after GC-RMA normalization (using e.g. the Limma package) and
looking at fitPLM images using the same background correction is a good
thing. But perhaps it is a bit unclear to me what you exactly want to
say.
And yes, I did use the option: background.method="GCRMA". However, I was
not aware of the threestep functionality. Thanks for the tip!
Regards,
Philip
-----Original Message-----
From: Ben Bolstad [mailto:bolstad at stat.Berkeley.EDU]
Sent: Tuesday, October 18, 2005 4:00 PM
To: Groot, Philip de
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] R-2.2 and BioConductor 1.7: changes in GC-RMA and
fitPLMprocedures
Hi,
It is good to hear that the results agree. The function bg.correct.gcrma
was introduced into the affyPLM package at the time of the previous BioC
release (1.6) as an aid to allow you to use the GC-RMA background with
the
fitPLM, threestep, threestepPLM etc (ie you could supply
background.method="GCRMA" as an argument to any of these functions). In
this latest release the GCRMA now includes bg.adjust.gcrma which does
essentially the same correction (as you have discovered) but with a
slightly different set of arguments. These differences will be removed
in
the future.
As an aside, I would be a little wary about combining the GCRMA
background
with fitPLM when your only interest is quality assessment.
Ben
On Tue, 18 Oct 2005, Groot, Philip de wrote:
> Hello,
>
> Just a small additional note. I just found out that both commands:
> bg.adjust.gcrma() and bg.correct.gcrma() return exactly the same
> results, thus solving my problem. I was confused by two different
> function calls that, in the end, do the same thing. I apologize for
any
> inconvenience.
>
> Regards,
>
> Dr. Philip de Groot
> Wageningen University
>
>
> -----Original Message-----
> From: Groot, Philip de
> Sent: Tuesday, October 18, 2005 10:16 AM
> To: bioconductor at stat.math.ethz.ch
> Subject: [BioC] R-2.2 and BioConductor 1.7: changes in GC-RMA and
> fitPLMprocedures
>
> Hello,
>
>
>
> I submit this message to the mailing list because I think that more
> people encounter the same problem. In general, when performing quality
> control calculations, performing fitPLM calculations (affyPLM package)
> is a good idea. Normalizing your data is also a good idea, so (in our
> situation) the same calculations are performed two times: fitPLM
> executes an GC-RMA background correction and the same thing is done
when
> applying the GC-RMA normalization. This was for me a reason to combine
> both calculations in a separate script in BioC 1.6, in which the
GC-RMA
> background correction is performed, used as input for the fitPLM
> procedure, and the further normalization steps are executed afterwards
> (this required digging in both scripts and perform the separate
required
> steps in a new script).
>
>
>
> Unfortunately, in BioC 1.7 things has changed significantly in such a
> way that it is more difficult to do the above things: all GC-RMA
> calculations (except the summarization) are performed in
> "bg.adjust.gcrma" while the fitPLM GC-RMA background correction is
> performed in "bg.correct.gcrma" (without an option to pass the
> previously calculated affinities to this function and to get the
> in-between GC-RMA values back).
>
>
>
> So, my question (request) is straightforward: are people working on a
> better integration of these two scripts, so that the end result of
> fitPLM can be used for the further GC-RMA normalization procedure?
This
> is not only more efficient, but also saves a considerable amount of
> computation time!
>
>
>
> Kind regards,
>
>
>
> Dr. Philip de Groot
>
> Wageningen University
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
>
More information about the Bioconductor
mailing list