Hi James,

The whole story is that my hard drive was broken and I only have backup
files left in csv files and scripts used to generate those files. But I did
not
put down the version number of R.gcrma,limma I used, neither could I
restore the old R working environment, so I have no way to check the
package.
versions. I think it is very important to add a line or two on my datafiles
with
the version numbers of those packages from now on.

What I did was simple:

data<-ReadAffy()
eset<-gcrma(data)
exprs2excel(eset,'somefilename')

When I compare the results from this script and the old one, I can not find
perfect
agreement. I installed bioconductor 2.0 last week, so the package should be
Affy
1.14.2, gcrma 2.8.1, limma 2.10.5. as I found out in
http://www.bioconductor.org/packages/2.0/bioc/

BTW, how do you print out the version number of a package in R? I googled
but
could not find the answer.

Thanks,
hongqing

On 8/23/07, James W. MacDonald <jmacdon@med.umich.edu> wrote:
>
> Hi Hongqing,
>
> Hongqing Li wrote:
> > Hi,
> >
> > I have been using limma and gcrma for microarray analysis for a while.
> > recently I have to reinstall my system so I update my R from 2.4 to
> 2.5.1
> > I don't know the version of limma,gcrma packages, but they were
> installed
> > as I install my old R 2.4.  However, when I run the same script to
> analyze
> > the same file I did last year, I got different results for both gcrma
> and
> > limma.
> > Although the difference is not dramatic. I plotted the scatter plot for
> > gcrma
> > summarized expression data from old analysis and new analysis, it
> supposed
> > to be a straight line, but on my plot the low expression values form a
> > slightly
> >  inflated data cloud around the diagonal line. For limma, only about 10
> > really
> > large or really small t statistics are strongly different from the old
> > analysis.
> > Is this a known issue for using different version of packages ?
>
> Well, yes. Probably. Since you don't know what versions you were using,
> nor the versions you are now using, it is impossible to say for sure
> (plus you don't say how you are analyzing the data, nor do you give a
> small reproducible example that we could try ourselves).
>
> However, Both limma and gcrma tend to change (limma perhaps more than
> gcrma) over time, as the maintainers improve both the implementation and
> underlying statistical methodology, so it is not unlikely that you would
> get 'not dramatic' changes in results with different versions.
>
> Best,
>
> Jim
> >
> > Thanks,
> > Hongqing
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
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> > Bioconductor@stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
> --
> James W. MacDonald, M.S.
> Biostatistician
> Affymetrix and cDNA Microarray Core
> University of Michigan Cancer Center
> 1500 E. Medical Center Drive
> 7410 CCGC
> Ann Arbor MI 48109
> 734-647-5623
>

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